In this study, an accurate convergence time of the supertwisting algorithm is proposed to build up a framework for nonaffine nonlinear systems’ finite-time control. The convergence time of the STA is provided by calculating the solution of a differential equation instead of constructing Lyapunov function. Therefore, precise convergence time is presented instead of estimation of the upper bound of the algorithm’s reaching time. Regardless of affine or nonaffine nonlinear systems, supertwisting control provides a general solution based on virtual control law (...) skill ensuring the output of the systems converges to the origin point at exact time. Benchmark tests are simulated to demonstrate the effectiveness and efficiency of the algorithm. (shrink)

Macroeconomic fluctuations in interest rates, exchange rates, and inflation can be considered sources of good or bad “luck” for corporate performance if management is unable to adjust operations to these fluctuations. Based on a sample of 2,091 US firms, we decompose the impacts of macroeconomic fluctuations on three measures of CEO compensation. Our study provides empirical support for the importance of considering macroeconomic fluctuations in designing CEO incentive schemes. It adds to the managerial power literature on moral hazard and CEO (...) compensation by pinpointing the obvious risk that the CEO in an asymmetric and non-linear reward system will be inclined to prioritize his/her own cash flow at the expense of fulfilling an assumed agency role. The policy conclusion for remuneration committees and board of directors is to filter out macroeconomic influences on performance to be rewarded whenever an asymmetric compensation scheme has been opted for. (shrink)

In this paper, a data-driven superheating control strategy is developed for organic Rankine cycle processes. Due to non-Gaussian stochastic disturbances imposed on heat sources, the quantized minimum error entropy is adopted to construct the performance index of superheating control systems. Furthermore, particle swarm optimization algorithm is applied to obtain optimal control law by minimizing the performance index. The implementation procedures of the presented superheating control system in an ORC-based waste heat recovery process are presented. The simulation results testify the effectiveness (...) of the presented control algorithm. (shrink)