The Cabin Pressure Control System is an essential part of the aviation environmental control system that ensures aircraft structure and flight crew safety. However, the CPCS usually has potential faults of sensors and actuators. To this end, a Simple Adaptive Control- based reconfiguration method is proposed to compensate for the above adverse effects. Some good pressure control performance of CPCS can be achieved by the basic pressure controller when the system is in (...) normal operation. A parallel feedforward compensator is designed to guarantee the closed-loop system’s stability and the almost strictly positive realness of the augmented system. Thus, the simple adaptive controller can be utilized for the CPCS. In particular, the reconfiguration system can update the control law online when the fault occurs without the system identification process. The reference model is obtained by mathematical model linearization after considering the mechanical characteristics of the CPCS. Extensive simulations under various typical fault scenarios are carried out throughout the entire flight envelope of the aircraft from take-off to landing. Simulation results validate the robustness and reconfiguration control capability of the proposed method. (shrink)

This article deals with detection and accommodation of sensor faults in longitudinal dynamics of an F8 aircraft model. Both the detection of the fault and reconfiguration of the failed sensor are done with the help of neural network-based models. Detection of a sensor fault is done with the help of knowledge-based neural network fault detection. Apart from KBNNFD, another neural network model is developed in this article for the reconfiguration of the failed sensor. A model-based approach of (...) the neural network is developed, which uses the radial basis function of the neural network. MBNN successfully does the task of providing analytical redundancy for the aircraft sensor. In this work, both detection and reconfiguration of a fault is done using neural networks. Hence, the control system becomes robust for handling sensor failures near steady state and reconfiguration is also faster. A generalized regression neural network, which is a type of radial basis network, is used for MBNN, which gives very efficient results for function approximation. An F8 aircraft model and C-Star controller, which improves its handling quality, are used for validation of the method involved. Models of F8 aircraft, C-Star controller, KBNNFD, and MBNN were developed using MATLAB/simulink. Successful implementation and simulation results are shown and discussed using Simulink. (shrink)

In the context of coronavirus pandemic, the face-recognition-based access control system has been intensively adopted to protect students’ and teachers’ health and safety in school. However, the impact of FACS, as a new technology, on students’ attitude toward accepting FACS has remained unknown from the psychological halo effect. Drawn on “halo effect” theory where psychological effects affect the sense of social identity and belonging, the present study explored college students’ sense of school identity and belonging in using (...) FACS during COVID-19 based on the technology acceptance model. Data collected from 391 college students was analyzed using SEM to verify the relationship among perceived usefulness, perceived ease of use, intention to use, school identity, and school belonging. The results show that PU and PEU can positively predict IU, and consequentially can positively predict school identity and school belonging. Our study expands the application of halo effect theory to study FACS acceptance based on TAM, and provides strong evidence to support the effect of school FACS during the pandemic. The findings of this study also suggest that FACS acceptance can enhance students’ sense of school identity and belonging. (shrink)

Morphogenesis is a key process in developmental biology. An important issue is the understanding of the generation of shape and cellular organisation in tissues. Despite of their great diversity, morphogenetic processes share common features. This work is an attempt to describe this diversity using the same formalism based on a cellular description. Tissue is seen as a multi-cellular system whose behaviour is the result of all constitutive cells dynamics. Morphogenesis is then considered as a spatiotemporal organization of cells (...) activities. We show how this formalism relies on Reaction–Diffusion/Positional Information approach and how it permits to generalize its modelling possibilities. Three quite different applications for concrete morphogenetic processes are presented. The first one is a model for epithelial invagination, the second is a model of cellular differentiation by local cell–cell signalling. The last example is the secondary radial growth of conifer trees. From the mathematical point of view, different modelling tools are used according to the specificity of each process. (shrink)

This paper is expected to introduce a novel memductor-based chaotic system. The local dynamical entities, such as the basic dynamical behavior, the divergence, the stability of equilibrium set, and the Lyapunov exponent, are all investigated analytically and numerically to reveal the dynamic characteristics of the new memductor-based chaotic system as the system parameters and the initial state of memristor change. Subsequently, an active control method is derived to study the synchronous stability of the novel (...) memductor-based chaotic system through making the synchronization error system asymptotically stable at the origin. Further to these, a memductor-based chaotic circuit is designed, realized, and applied to construct a new memductor-based secure communication circuit by employing the basic electronic components and memristor. Furthermore, the design principle of the memductor-based chaotic circuit is thoroughly analyzed and the concept of “the memductor-based chaotic circuit defect quantification index” is proposed for the first time to verify whether the chaotic output is consistent with the mathematical model. A good qualitative agreement is shown between the simulations and the experimental validation results. (shrink)

This paper is concerned with the optimal output feedback control problem for networked control systems with Markovian packet losses. In this paper, the packet losses occur both between the sensor and controller and between the controller and actuator. Moreover, the packet loss channels are described with two-state Markov chains. Since the precise state information cannot be obtained, thus an optimal recursive estimator is designed. Furthermore, by adopting the dynamic programming approach, we derive the optimal output feedback control, (...) which is based on the solution to a given modified Riccati equation. The obtained results can be seen as an important implementation of the control theory for NCSs with unreliable communication channels. (shrink)

Attachment is an emotional bond between two people where one seeks care from the other. In the prototypical case, the child attaches to their mother. The most recent theoretical developments point out that attachment is multidimensional – meaning that the phenomenon pertains to multiple domains related to the relationship with the caregiver. However, researchers have so far modeled attachment computationally by mostly adopting a classical categorical (as opposed to dimensional) standpoint that sees the system as controlling caregiver proximity. In (...) contrast, we adopt here adimensional perspective(DP) and consider dimensions to be the system’s set-goals. We hypothesize that the resulting multidimensional controller should lead to valid (or even better) models of the phenomenon. To start testing this hypothesis, we built a DP-informed agent-based model of attachment inspired by the widely-studied Strange Situation Procedure. In this context, child and mother show the nature of attachment bonds through their behavioral and emotional expressions. By modeling them as point-agents moving in a two-dimensional arena, we simulated child-mother interactions for the avoidant and ambivalent attachment dimensions. The generated dynamical patterns – characterized by the alternation between approach and exploration – matched those described in the attachment literature, thereby confirming the implementability and validity of the DP. (shrink)

Though the formal coherence and empirical utility of Marcello Barbieri’s concept of organic code have been starting to become established, a general conception of how the semantics of organic codes is related to the pragmatics of their use is still missing. Barbieri took a first step towards such a conception by distinguishing three types of semiosis in living systems: manufacturing, signalling, and interpretive semiosis. This paper integrates Barbieri’s distinction into Roman Jakobson’s systematization of possible functions of messages in order to (...) propose a general conception of possible types of semiosis in living systems. As a result, Barbieri’s thesis that manufacturing and signalling semiosis are basic types of semiosis, can be confirmed and completed communication-theoretically. (shrink)

Ethical aspects of management control systems are attracting increasing attention among scholars and practitioners. Much of the work centers on their aims. We complement this scholarship by applying the ethical principle of “no harm,” i.e., non-maleficence, to examine how those aims are achieved. We illustrate this approach by exploring the effects of four MCS designs on job-related stress drawing on the differentiation of stress into two dimensions: a challenge and a threat dimension. Results from a lagged field-survey with (...) 471 managers and employees from the UK and the U.S. support key predictions and offer first insights into designing MCS based on a “no harm” ethics. Our study highlights the benefits of interdisciplinary research in business ethics and hopefully encourages more work on MCS from a perspective based on the non-maleficence principle. (shrink)

This paper presents a problem of observer-based adaptive fuzzy predefined performance control of a class of nonlinear pure-feedback systems with input delay and unknown control direction. Compared with the existing research, a novel predefined performance controller is proposed, which relaxes the assumption that the initial error is known. In addition, it is difficult to design the controllers due to input delay and nonaffine properties of the pure-feedback systems, which can be simplified by Pade approximation. Moreover, dynamic surface (...) control and Nussbaum functions are applied to overcome the calculation explosion caused by repeated differentiations and unknown control direction, respectively. Based on the above methods, an adaptive fuzzy predefined performance controller is proposed, and it is proved that all the signals of a closed-loop system are semiglobally uniformly ultimately bounded. The tracking errors converge within a predefined range, while the observer estimation errors converge within a small zero region. Finally, the simulation results demonstrate the effectiveness of the proposed control system. (shrink)

The management control system aids administrators in guiding a business toward its organizational plans; as a result, management control is primarily concerned with the execution of the plan and plans. Financial and nonfinancial criteria are used to create management control systems. The financial element focuses on net income, earnings, and other financial metrics. The two components of leadership strategy in this study are cost and differentiation, which highlight the strategy of differentiation in attaining higher quality due (...) to the robust strategy’s attention on a particular area of the company. In this study, we presented a novel method named deep interaction neural network to predict the performance of the manufacturing companies based on their leading competitors using features cost leadership and differentiation strategies. Moreover, the management control system is classified into two financial and nonfinancial factors based on machine learning methods. Based on the results, the presented factors can accurately estimate the company’s performance based on management control criteria with a 93.48% R-square. Moreover, it can be seen that the DT method is presented with higher classification performance values. (shrink)

This paper investigates the antidisturbance formation control problem for a class of cluster aerospace unmanned systems suffering from multisource high-dynamic uncertainties. Firstly, to estimate and compensate the uncertainties existing in CAUS coordinate dynamics, an adaptive antidisturbance formation control law, which is combined by a robust adaptive control law and the second order disturbance observer, has been designed. Secondly, aiming at the adverse influences caused by the nonlinear time-varying nonlinearities existing in the formation flight dynamics, the radial basis (...) function neural network is introduced. Furthermore, considering the rapidly varying characteristics of the aforementioned formation flight nonlinearities, a novel board RBFNN has been constructed and utilized to improve the approximation and compensation performance. In virtue of the fusing of the B-RBFNN and the second-order disturbance observer-based adaptive formation control law, the rapid response rate and the higher control accuracy of the formation control system can be achieved. As a result, a novel B-RBFNN-based intelligence adaptive antidisturbance formation control algorithm has been established for CAUS trajectory coordination and formation flight. Numerical simulation results are proposed to illustrate the effectiveness and advantages of the proposed B-RBFNN-based intelligent adaptive formation control method for the CAUS. (shrink)

The fault ride-through capability and fault current issues are the main challenges in doubly fed induction generator- based wind turbines. Application of the bridge-type fault current limiter was recognized as a promising solution to cope with these challenges. This paper proposes a nonlinear sliding mode controller for the BFCL to enhance the FRT performance of the DFIG-based WT. This controller has robust performance in unpredicted voltage sag level and nonlinear features. Theoretical discussions, power circuit, and nonlinear control (...) consideration of the SMC-based BFCL are conducted, and then, its performance is verified through time-domain simulations in the PSCAD/EMTDC environment. To reduce the chattering phenomenon and decrease the reaching time, it used the exponential reaching law for designed SMC. Also, the SMC-based BFCL performance is compared with the conventional and PI controller-based BFCL for both symmetrical and asymmetrical short-circuit faults. Simulation results reveal that the SMC-based BFCL provides better performance compared with the conventional and PI controller-based BFCL to enhance the FRT. (shrink)

A model predictive control method based on recursive backpropagation neural network and genetic algorithm is proposed for a class of nonlinear systems with time delays and uncertainties. In the offline modeling stage, a multistep-ahead predictor with GA-RBP neural network is designed, where GA-BP neural network is used as a one-step prediction model and GA is employed to train the initial weights and bias of the BP neural network. The incorporation of GA into RBP can reduce the possibility of (...) the BP neural network falling into a local optimum instead of reaching global optimization. In the online optimizing stage, a multistep-ahead GA-RBP neural network predictor and an improved gradient descent method are proposed to efficiently solve the online optimization problem of nonlinear MPC by minimizing a modified quadratic criterion. The designed MPC strategy can avoid information loss while linearizing the controlled system and computing the Hessian matrix and its inverse matrix. Experimental results show that the proposed approach can reduce the computational burden and improve the performance of MPC for the solution of nonlinear controlled systems. (shrink)

The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the (...) solution of stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results. (shrink)

The spread of epidemics, especially COVID-19, is having a significant impact on the world. If an epidemic is not properly controlled at the beginning, it is likely to spread rapidly and widely through the coexistence relationship between natural and social systems. A university community is a special, micro-self-organized social system that is densely populated. However, university authorities in such an environment seem to be less cautious in the defence of an epidemic. Currently, there is almost no quantitative research on (...) epidemic spreading and response strategies in universities. In this paper, a case study of a university community is considered for a simulation of an infection evolving after an epidemic outbreak based on the method of system dynamics of the three stages. The results show the following: By improving the speed of the initial emergency response, the total number of patients can be effectively controlled. A quarantine policy helps to slow down the evolution of infection. The higher the isolation ratio, the higher the cost; therefore, the isolation ratio should be optimized. It is important to make emergency plans for controlling epidemic spreading and carry out emergency drills and assessments regularly. According to the results of this study, we suggest an emergency management framework for public health events in university communities. (shrink)

This work investigates the finite-time control problem for a nonlinear four-tank cross-coupled liquid level system by the port-controlled Hamiltonian model. A fixed-free methodology is exhibited which can be used to simplify the controller design procedure. To get an adjustable convergent gain of the finite-time control, a feasible technique named damping normalization is proposed. A novel parameter autotuning algorithm is given to clarify the principle of choosing parameters of the PCH method. Furthermore, a finite-time controller is designed by (...) a state-error desired Hamiltonian function, and the relationship between the settling time and a parameter is given, which can be applied in practical engineering easily to adjust the settling time according to the industrial need. Finally, simulation and experimental results verify the effectiveness of the proposed algorithm. (shrink)

In this paper, a mathematical model was used to evaluate a dynamical hybrid system for optimizing and controlling the efficacy of plant-based protein in aquafeeds. Fishmeal, raw rapeseed meal, and a fermented meal with yeast and fungi were used as test ingredients for the determination of apparent digestibility coefficients of dry matter, crude protein, crude lipid, energy, and essential amino acids for olive flounder using diets containing 0.5% Cr2O3 as an inert indicator. Among all ingredients tested, FM had (...) the maximum ADC of dry matter, and energy. Fermented meals showed higher ADC. Amino acid digestibility reflects protein digestibility in most cases. Interestingly, protease, lipase, and amylase activities were better expressed in RM-Koji, RM-Yeast, and FM over RM, respectively. The current results deliver important information on nutrients and energy bioavailability in raw and fermented RM, which can be implemented to accurately formulate applied feeds for olive flounder. Compared with other applicable systems, the complexity of the approach implemented has been considerably reduced. (shrink)

In this study, an adaptive output feedback fault tolerant control scheme is proposed for a class of multi-input and multioutput nonlinear systems with multiple constraints. The neural network is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator (...) faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller. (shrink)

This paper suggests an online solution for the optimal tracking control of robotic systems based on a single critic neural network -based reinforcement learning method. To this end, we rewrite the robotic system model as a state-space form, which will facilitate the realization of optimal tracking control synthesis. To maintain the tracking response, a steady-state control is designed, and then an adaptive optimal tracking control is used to ensure that the tracking error can (...) achieve convergence in an optimal sense. To solve the obtained optimal control via the framework of adaptive dynamic programming, the command trajectory to be tracked and the modified tracking Hamilton-Jacobi-Bellman are all formulated. An online RL algorithm is the developed to address the HJB equation using a critic NN with online learning algorithm. Simulation results are given to verify the effectiveness of the proposed method. (shrink)

The paper presents a framework to realise “meaningful human control” over Automated Driving Systems. The framework is based on an original synthesis of the results of the multidisciplinary research project “Meaningful Human Control over Automated Driving Systems” lead by a team of engineers, philosophers, and psychologists at Delft University of the Technology from 2017 to 2021. Meaningful human control aims at protecting safety and reducing responsibility gaps. The framework is based on the core assumption (...) that human persons and institutions, not hardware and software and their algorithms, should remain ultimately—though not necessarily directly—in control of, and thus morally responsible for, the potentially dangerous operation of driving in mixed traffic. We propose an Automated Driving System to be under meaningful human control if it behaves according to the relevant reasons of the relevant human actors (tracking), and that any potentially dangerous event can be related to a human actor (tracing). We operationalise the requirements for meaningful human control through multidisciplinary work in philosophy, behavioural psychology and traffic engineering. The tracking condition is operationalised via a proximal scale of reasons and the tracing condition via an evaluation cascade table. We review the implications and requirements for the behaviour and skills of human actors, in particular related to supervisory control and driver education. We show how the evaluation cascade table can be applied in concrete engineering use cases in combination with the definition of core components to expose deficiencies in traceability, thereby avoiding so-called responsibility gaps. Future research directions are proposed to expand the philosophical framework and use cases, supervisory control and driver education, real-world pilots and institutional embedding. (shrink)

This article investigates an adaptive neural network control algorithm for marine surface vessels with time-varying output constraints and unknown external disturbances. The nonlinear state-dependent transformation is introduced to eliminate the feasibility conditions of virtual controller. Moreover, the barrier Lyapunov function is used to achieve time-varying output constraints. As an important approximation tool, the NN is employed to approximate uncertain and continuous functions. Subsequently, the disturbance observer is structured to observe time-varying constraints and unknown external disturbances. The novel strategy can (...) guarantee that all signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, the simulation results verify the benefit of the proposed method. (shrink)

We present a distributed control modeling approach for an automated manufacturing system based on the dynamics of one-dimensional cellular automata. This is inspired by the fact that both cellular automata and manufacturing systems are discrete dynamical systems where local interactions given among their elements can lead to complex dynamics, despite the simple rules governing such interactions. The cellular automaton model developed in this study focuses on two states of the resources of a manufacturing system, namely, busy (...) or idle. However, the interaction among the resources such as whether they are shared at different stages of the manufacturing process determines the global dynamics of the system. A procedure is shown to obtain the local evolution rule of the automaton based on the relationships among the resources and the material flow through the manufacturing process. The resulting distributed control of the manufacturing system appears to be heterarchical, and the evolution of the cellular automaton exhibits a Class II behavior for some given disordered initial conditions. (shrink)

In recent years a series of developments in apparently loosely coupled domains have contributed to the development of new and vital perspectives on how to manage complex social systems such as corporations. These developments include improved communications technologies, increased awareness by constituencies of their potentials for influencing corporate behaviour, increased complexity and reduced transparency in large, heterogeneous organisations, a corresponding reduction in the capacity of traditional accounting and reporting systems to reflect organisational performance, new demands from employees as to their (...) work environments, from customers as to ecological and ethical sensitivity, from civil society and governments as to social and environmental accountability etc.A result is a major shift in the way organisations are choosing to observe themselves and to describe, measure, evaluate and report on their performance. From a focus on efficiency and control to a values-based perspective on management, corporate identity and success. And from a focus on legal compliance and financial performance to a focus on corporate social and ethical responsibility and accountability. (shrink)

In this paper, a repetitive control scheme of a 2-DOF robotic manipulator based on the improved cubic B-spline curve is proposed. Firstly, a repetitive controller for robotic manipulator is designed, which is composed of an iterative controller and disturbance observer. Then, an improved B-spline optimization scheme is introduced to divide the task of the robotic manipulator into three intervals. A correction function is added to each interval of cubic spline interpolation. Finally, a variety of cases are designed and (...) simulated by MATLAB. The experimental results show that, compared with the conventional B-spline, the improved B-spline has better performance in tracking accuracy and smoothness of motion trajectory. By changing the mechanism of the manipulator, the cases of different weights and lengths are designed. The experimental results in these cases show that the proposed scheme can be applied to most of the 2-DOF robotic manipulator control systems. (shrink)

A novel conservative chaotic system with no equilibrium is investigated in this study. Various dynamics such as the conservativeness, coexistence, symmetry, and invariance are presented. Furthermore, a partial-state feedback control scheme is proposed, and the stable domain of control parameters is analyzed based on the degenerate Hopf bifurcation. In order to verify the numerical simulation analysis, an analog circuit is designed. The simulation results show that the output of the analog circuit system can reproduce (...) the numerical simulation results and verify the correctness of the theoretical analysis. (shrink)

The system reachability set is calculated by covering all possible behaviours of the system through a finite number of simulation steps to ensure that the system trajectory stays within a set safety region. In this paper, the theory of the game method is applied to the design of the controller, a very small controller is designed, and good control results are obtained by simulation. The system gradually shows a divergent trend and cannot achieve stable (...) control. A multihop channel reservation Medium Access Control protocol based on a parallel mechanism is proposed. The multihop channel reservation mechanism is proposed based on periodic node sleep, and the node uses the reservation frame to make the reservation of the channel and transmits the data according to the reservation information; the parallel mechanism is used to make the reservation information and data transmission simultaneously. (shrink)

The pressure control for a liquid nature gas ship is vital for the cargo handling system which is a nonlinear, unstable, and controllable complex system accompanied by the dynamics of time delay. To improve the control effect, this article proposed a robust controller based on closed-loop gain shaping algorithm by mirror-mapping approach. In addition, the complete mechanism models for the system are established to predict the changes of temperature, pressure, and liquid inventory in the (...) cargo tank. The heat exchanges and evaporation of liquid are also considered. By collecting the data from the LNG ship “Dapeng,” the system models are validated. At the same time, the comparative experiment is introduced to verify the reliability and effectiveness. The scheme has been compared with the 2-DOF structure control law of modified Smith predictor. The comparative experimental results show that the scheme proposed in this note has a strong disturbance rejection ability and steady-state performance. The controller designed in this note has advantages of simplified construction method, satisfactory control effect and robustness. (shrink)

This paper presents a novel fractional-order PID controller tuning strategy based on Bode’s optimal loop shaping which is commonly used for LTI feedback systems. Firstly, the controller parameters are achieved based on flat phase property and Bode’s optimal reference model, so that the controlled system is robust to gain variations and can achieve desirable transient performance according to various control requirements. Then, robustness analysis of the controlled system is carried out to support the results. (...) Furthermore, the parameter setting is analyzed to demonstrate the superiority of the proposed controller. At last, some simulation examples are shown to verify the accuracy and usefulness of the proposed control strategy. The proposed fractional-order PID controller does not have any restriction on the controlled plant, so it can be widely applied on both integer-order and fractional-order systems. (shrink)

This paper describes the design of a control and management network (orderwire) for a mobile wireless Asynchronous Transfer Mode (ATM) network. This mobile wireless ATM network is part of the Rapidly Deployable Radio Network (RDRN). The orderwire system consists of a packet radio network which overlays the mobile wireless ATM network, each network element in this network uses Global Positioning System (GPS) information to control a beamforming antenna subsystem which provides for spatial reuse. This paper also (...) proposes a novel Virtual Network Configuration (VNC) algorithm for predictive network configuration. A mobile ATM Private Network-Network Interface (PNNI) based on VNC is also discussed. Finally, as a prelude to the system implementation, results of a Maisie simulation of the orderwire system are discussed. (shrink)

Virtual enterprise is a dynamic alliance of businesses, in which multiple members undertake joint research, development, manufacturing, operation, etc. The complexity of the relationship between business members, coupled with many new technologies or methods applied in the alliance operation, leads to more uncertain factors and difficulties in the operation and risk management of the virtual enterprise. The distributed decision-making model is a fast and effective decision-making model, in which dispersed intellectual resources and information resources are dynamically integrated through virtual organization (...) forms and operating mechanisms, and the dynamic reorganization, result evaluation, and synthesis of the decision-making system are realized by certain control rules. On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of the risk control of virtual enterprise; elaborated the development background, current status, and future challenges of distributed decision-making model; introduced the related works of decision-making variable calculation and constraint determination; constructed a risk control model for virtual enterprise based on distributed decision-making model; analyzed the multiobjective model and interval programming model of risk control; established a risk control approach for virtual enterprise based on distributed decision-making model; performed the optimal allocation of risk control funds and the selective optimization of backup allies; and finally conducted a case analysis. The study results show that, in view of the diversity of relationships between alliance businesses and the complexity of the distribution of cooperative areas, the distributed decision-making model can more reasonably describe the relationship between alliance members and accurately control the risks of virtual enterprise from multiple angles, which can effectively manage the risks of virtual enterprise. The study results of this paper provide a reference for further research on the risk control of virtual enterprise based on distributed decision-making model. (shrink)

In this paper, a concise robust control law based on Backstepping for marine engine speed regulation is presented with the uniform asymptotic stability of the closed-loop system proved by Lyapunov synthesis, and the control parameters have obvious physical meaning. Furthermore, parameter determination method is given by virtue of closed-loop gain shaping algorithm. To overcome the perturbation due to load or interference change, variable universe fuzzy inference is introduced to optimize the control system on-line. Compared (...) with the existing research literature, the design method and performance of the controller are more in line with the ocean engineering practice. The results of the simulations of the proposed controller are presented and compared. (shrink)

Social anxiety disorders are among the most prevalent mental disorders, with high impact on the life of an affected social system and its individual social system members. We developed a manualized disorder-specific integrative systemic and family therapy for SAD, and evaluated its feasibility in a pilot randomized controlled trial. The ISFT is inspired by Helm Stierlin’s concept of related individuation developed during the early 1980s, which has since continued to be refined. It integrates solution-focused language, social network diagnostics, (...) and genogram work, as well as resource- and problem orientation for both case conceptualization and therapy planning. Post-Milan symptom prescription to fluidize the presented symptoms is one of the core interventions in the ISFT. Theoretically, the IFST is grounded in radical constructivism and “Cybern-Ethics,” multi-directional partiality, and a both/and attitude toward a disorder-specific vs. non-disorder-specific therapy approach. SAD is understood from the viewpoint of social systems theory, especially in adaptation to a socio-psycho-biological explanatory model of social anxiety. In a prospective multicenter, assessor-blind pilot RCT, we included 38 clients with SAD : 18 patients participated in the ISFT, and 20 patients in Cognitive Behavioral Therapy. Within-group, simple-effect intention-to-treat analyses showed significant reduction in social anxiety, while intention-to-treat mixed-design ANOVA demonstrated the advantage of ISFT. Per-protocol analyses supported these results. The remission rate based on blind diagnosticians’ ratings was good to satisfactory ; this has yet to be verified in a subsequent confirmatory RCT. The article will present the ISFT rationale and manual, including a special focus on multi-person settings, and the central findings from our pilot RCT. (shrink)

The quality of service of a user in user-centric unmanned aerial vehicle group is degraded by complex cochannel interference; hence, a cooperative game power control algorithm in UUAVG is proposed. The algorithm helps to establish a downlink power control model of the UUAVG, construct a product of the signal to interference noise ratio function of each user as a utility function of the cooperative game, and deduce the optimal power control scheme using the Lagrange function. This scheme (...) reduces the interference of the service unmanned aerial vehicle to edge users and improves the communication quality of all the users as well as the throughput of the entire system. Simulation results show that the average throughput of the CGPC algorithm improved by 10.32% compared with the traditional Stackelberg Game based Nonunified Pricing Power Control algorithm. This shows that the CGPC algorithm can effectively reduce the transmission power of the cooperative UAV and enhance the capacity of the entire system, ensuring communication quality. (shrink)

In this paper, a normalized robust FOPID controller regulation algorithm is proposed. Only one parameter k is necessary to be tuned in the controller regulation process, so the proposed control algorithm is convenient to be applied on both fractional-order systems and integer-order systems. A robustness evaluation function is constructed based on the small gain theorem. Larger robustness evaluation function value will help the system achieve better robustness performance. Another parameter, β, is also available to serve as a (...) tuning knob when larger robust evaluation function value is needed. Therefore, the controlled systems can be stabilized and can achieve quite satisfactory robust control performance using the proposed algorithm. The corresponding robust analysis results are obtained according to different conditions in the discussion. For a special case of widely used fractional-order systems, the FOPI and FOID controllers are presented based on the same tuning scheme together with their robustness discussion. Some examples are shown to verify the robustness of systems controlled by the proposed algorithm. (shrink)

This research, couched in the resourcebased view of the firm, investigates the potential for reducing an organization's decision uncertainty within its structural equation modeling, we empirically test if organizational design can reduce the perceived uncertainty related to an IC context, which we refer to as knowledge uncertainty. We found evidence that decentralization and technology infrastruture support a resultsbased IC mangement contrl system which in turn is associated with reduced support a good overall fit for our model. Our findings suggest (...) that if managers structure their organizational control systems appropriately for developing IC capabilities, these systems can lead to reduced internal uncertainty regarding human, structural, and relational capital. (shrink)

At present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the desired trajectory of human hip and knee joints. In this paper, the experimental platform of lower limb exoskeleton rehabilitation robot is built, and the control system software and hardware design and (...) robot prototype function test are carried out. On this basis, a series of experiments are carried out to verify the rationality of the robot structure and the feasibility of the control method. Firstly, the dynamic model of the lower limb exoskeleton robot is established based on the structure analysis of the human lower limb; secondly, the servo control model of the lower limb exoskeleton robot is established based on the iterative learning control algorithm; finally, the exponential gain closed-loop system is designed by using MATLAB software. The relationship between convergence speed and spectral radius is analyzed, and the expected trajectory of hip joint and knee joint is obtained. The simulation results show that the algorithm can effectively improve the gait tracking accuracy of the lower limb exoskeleton robot and improve the follow-up performance of the human-machine system. (shrink)

A varied air volume air-conditioning system comprises diverse input and/or output disturbances, which are commonly nonlinear, with large lag and uncertainty. Based on the traditional control methods, testing the controlling parameters of a VAV air-conditioning system is challenging. Sliding mode control could improve the robustness of the system due to the adaptive capacity of disturbance rejection. Moreover, the fuzzy algorithm could be employed to determine the stability of a sliding control system by (...) adjusting the parameters in the approach rate, reducing the switching frequency, and weakening chatter. Fuzzy sliding mode control is investigated in this paper to improve the performance of a VAV air-conditioning system. Simulation results verify that the sliding mode control is suitable for a VAV air-conditioning system to achieve good adaptability and robustness considering the influence of multiple external variable disturbances. In addition, the chattering of the system is improved after the introduction of fuzzy control. (shrink)

In this paper, a 3D jerk chaotic system with hidden attractor was explored, and the dissipativity, equilibrium, and stability of this system were investigated. The attractor types, Lyapunov exponents, and Poincare section of the system under different parameters were analyzed. Additionally, a circuit was carried out, and a good similarity between the circuit experimental results and the theoretical analysis testifies the feasibility and practicality of the original system. Furthermore, a robust feedback controller was designed (...) class='Hi'>based on the finite-time stability theory, which guarantees the synchronization of 3D jerk master-slave system in finite time and asymptotically converges to the origin. Finally, we also give verification for the discussion in this paper by numerical simulation. (shrink)

The event-triggered consensus control for leader-following multiagent systems subjected to external disturbances is investigated, by using the output feedback. In particular, a novel distributed event-triggered protocol is proposed by adopting dynamic observers to estimate the internal state information based on the measurable output signal. It is shown that under the developed observer-based event-triggered protocol, multiple agents will reach consensus with the desired disturbance attenuation ability and meanwhile exhibit no Zeno behaviors. Finally, a simulation is presented to verify (...) the obtained results. (shrink)

An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. (...) Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness. (shrink)

A tracking control algorithm of nonlinear multiple agents with undirected communication is studied for each multiagent system affected by external interference and input saturation. A control design scheme combining iterative learning and adaptive control is proposed to perform parameter adaptive time-varying adjustment and prove the effectiveness of the control protocol by designing Lyapunov functions. Simulation results show that the high-precision tracking control problem of the nonlinear multiagent system based on adaptive iterative (...) learning control can be well realized even when the input is saturated. Finally, the validity of the proposed algorithm is verified by numerical analysis. (shrink)

Due to the excellent approximation ability, the neural networks based control method is used to achieve adaptive consensus of the fractional-order uncertain nonlinear multiagent systems with external disturbance. The unknown nonlinear term and the external disturbance term in the systems are compensated by using the radial basis function neural networks method, a corresponding fractional-order adaption law is designed to approach the ideal neural network weight matrix of the unknown nonlinear terms, and a control law is designed eventually. (...) According to the designed Lyapunov candidate function and the fractional theory, the systems stability is proved, and the adaptive consensus can be guaranteed by using the designed control law. Finally, two simulations are shown to illustrate the validity of the obtained results. (shrink)

Blockchain is a pioneering technology that allows the creation of innovative information exchange ecosystems thanks to unique properties, such as immutability, distribution and transparency. By combining this technology with the emergent internet of things (IoT), many innovative business models can be created. The main objective of this work is to present the design and an initial implementation of a decentralized rental system that takes advantage of smart contracts developed on a public blockchain, combined with the potential of the IoT (...) and its intimate relationship with cyber-physical systems. The logic to be implemented in the blockchain is applied in this paper by using the Ethereum programming language, so that the developed application covers the entire car rental process offered in traditional web applications, but adding more autonomy, functionalities and ease of use for both lessees and lessors. Following Ethereum application development guidelines, all business logic is located in the smart contracts implemented in the network, where they can be used to control the car rental system. While this is a work in progress, the results obtained in the first proof of concept have been very promising. (shrink)

An iterative learning robust fault-tolerant control algorithm is proposed for a class of uncertain discrete systems with repeated action with nonlinear and actuator faults. First, by defining an actuator fault coefficient matrix, we convert the iterative learning control system into an equivalent unknown nonlinear repetitive process model. Then, based on the mixed Lyapunov function approach, we describe the stability of the nonlinear repetitive mechanism on time and trial indices and have appropriate conditions for the repeated (...) class='Hi'>control system’s stability in terms of linear matrix inequality theory. Through LMI techniques, we have obtained satisfactory results and controller stability, and robustness against fault tolerance is also discussed in detail. Finally, the simulation results of the output tracking control of the two exemplary models verify the effectiveness of the proposed algorithm. (shrink)

The H ∞ performance of a class of T-S fuzzy systems with Markovian-jump parameters is analyzed. A state feedback controller is designed for T-S fuzzy systems with Markovian-jump parameters. First, a new modal-dependent Lyapunov function composed of closed-loop functions is constructed, which can fully use system status information. Based on this function, the stability conditions with less conservatism are given by linear matrix inequalities. At the same time, a design algorithm for a state feedback controller is proposed for (...) the Markovian-jump-parameters T-S fuzzy systems, which ensures the system’s stability under the condition of H ∞ − γ performance. Simulation results demonstrate that the mentioned method is accurate and practical. (shrink)

System security is essential for the operation of the island microgrid. However, the system security is generally threatened due to the presence of physical uncertainties and cyber attacks. In this article, a novel sliding mode load control strategy is proposed for the microgrid to mitigate cyber attacks and physical uncertainties. Firstly, a high-order disturbance observer is designed to estimate the unmeasurable factors in the microgrid. Secondly, a HODO-based sliding mode control strategy is proposed where the (...) estimated value observed by the HODO is applied to the sliding mode surface and control law. It can better guarantee the security of the isolated microgrid. Then, the stability of the HODO-based SMC is demonstrated by Lyapunov stability theory. Finally, simulation results show that the proposed control strategy has excellent control performance. (shrink)

The aerial manipulator is a complex system with high coupling and instability. The motion of the robotic arm will affect the self-stabilizing accuracy of the unmanned aerial vehicles. To enhance the stability of the aerial manipulator, a composite controller combining conventional proportion integration differentiation control, fuzzy theory, and neural network algorithm is proposed. By blurring the attitude error signal of UAV as the input of the neural network, the anti-interference ability and stability of UAV is improved. At the (...) same time, a neural network model identifier based on Maxout activation function is built to realize accurate recognition of the controlled model. The simulation results show that, compared with the conventional PID controller, the composite controller combined with fuzzy neural network can improve the anti-interference ability and stability of UAV greatly. (shrink)

This paper presents an adaptive fuzzy sliding-mode controller for multiple Euler–Lagrange systems communicated with directed topology. Based on the graph theory and Lyapunov–Krasovskii functions, a delay-dependent sufficient condition for the existence of sliding surfaces is given in terms of linear matrix inequalities. The asymptotic stability is analyzed by using the Lyapunov method in the presence of unknown parametric dynamics, actuator faults, and time-varying delays. The usage of adaptive techniques is to adapt the unknown parameters so that the objective of (...) globally asymptotic stability is achieved. Finally, simulation results are provided to illustrate the effectiveness of the proposed control scheme. (shrink)

PurposeThe purpose of this paper is to examine the social impacts of “silent control” of individuals by means of the architecture of dataveillance systems. It addresses the question whether individuals, in reality, can actually determine autonomously the kinds of information that they can acquire and convey in today's dataveillance environments. The paper argues that there is a risk of a “counter‐control revolution” that may threaten to reverse the “control revolution” described by Shapiro.Design/methodology/approachUsing relevant business cases, this paper (...) describes the nature of dataveillance systems, then it examines situations in which the intellectual freedom of individuals is silently constrained by the architecture of such systems. This analysis leads to the conclusion that individuals in today's information society face the risk of a “counter‐control revolution” that can threaten their intellectual freedom. Given this troubling conclusion, the present paper addresses the challenges of establishing socially acceptable dataveillance systems.FindingsIntentionally or unintentionally, the architecture of dataveillance systems determines what kinds of information an individual can access or receive. This means that social sorting occurs based upon the processing of personal information by dataveillance systems; and, as a result, individuals' intellectual freedom could be constrained without their realising that it is happening. Under this circumstance, the ability of individuals to control the transmission and flow of information, recently made possible by the “control revolution”, already has been compromised by business organisations that operate dataveillance systems. It is business organisations, and not the individuals themselves, that control the kinds of information that individuals are able to acquire and transmit.Originality/valueThis paper provides an analysis of social risks caused by the architecture of dataveillance systems, and it introduces the concept of a “counter‐control revolution”. These contributions provide a good starting point to evaluate the social impacts of dataveillance systems and to establish better, more socially acceptable dataveillance systems. (shrink)