Prescribed Performance Adaptive Control for a Nonlinear Aeroelastic System with Input Constraint

Abstract

A constrained prescribed performance compensation controller is proposed for a nonlinear aeroelastic system in the presence of wind gust, system uncertainties, and input saturation. To deal with the effects of the nonsmooth saturation nonlinearity, an approximate saturation function is introduced into the controller design, which can smoothly approximate the real saturation with arbitrarily prescribed precision. Specifically, by designing the prescribed performance function, a fixed-time control framework is designed to ensure that the closed-loop system has the prescribed tracking performance. The designed control algorithm can not only compensate the adverse effect caused by disturbances and uncertainties but also restrain the excessive amplitude of control input. Finally, the stability analysis shows that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded via the Lyapunov stability analysis method, and simulation results are presented to demonstrate the feasibility and effectiveness of the proposed method.

Optimal Reconstruction of Single-Pixel Images through Feature Feedback Mechanism and Attention

“…Feedback is defined as the output of the system as part of the input during causal iteration, which in turn influences the work of the system [33][34][35][36]. In DL, the feedback mechanism can support the network in using high-level features of the output to optimize the weights of the previous convolution kernel.…”