A novel prescribed performance controller for strict-feedback nonlinear systems with input constraints. (January 2023) - Zhao, Nan-Nan; Zhang, Ai-Min; Ouyang, Xin-Yu; Wu, Li-Bing; Xu, Hai-Bo
Abstract: This paper is devoted to the prescribed performance control (PPC) for a class of strict-feedback nonlinear systems with input saturation constraints. With the help of an improved tuning function, the system can achieve the desired steady-state and transient performance in the pre-designed time. A new error transformation function is introduced, which has inherent robustness, so it does not need to use any approximation technique or calculate the analytical derivative. Compared with the relevant results, the proposed scheme has the same lower complexity, but better transient and steady-state performance, although there exists uncertain nonlinearity and uncertain disturbances in the system. Finally, the correctness of the above algorithm is verified by simulation experiments. Highlights: An anti-hyperbolic tangent function is used to deal with the unknown nonlinearity. The output error can be constrain to the preset band in finite time. The controller is more effective in structure and computation than others. The method has better transient and steady-state performance than similar studies.