Model‐free adaptive integral sliding mode constrained control with modified prescribed performance

Abstract

In this work, a novel model‐free adaptive integral sliding model constrained control strategy with modified prescribed performance is proposed for nonlinear nonaffine systems via full‐form dynamic linearization (FFDL). Firstly, a generalized nonlinear nonaffine system with external disturbance is transformed into an affine system via the FFDL method, which contains a linearly parametric term affine to the control input and preceding output data, and an unknown nonlinear time‐varying term. Then, an adaptive estimation method and a discrete‐time extended state observer (DESO) are used to estimate the pseudo gradient (PG) vector and lumped uncertainties, respectively. Furthermore, an integral sliding mode control scheme containing a modified prescribed performance function and an anti‐windup compensator is designed to keep the output tracking error in the prescribed bound without causing any asymmetric offset error in the steady‐state and to suppress the influence of input saturation. Simulation results demonstrate the superiority of the proposed control scheme.

An analytical adaptive optimal control approach without solving HJB equation for nonlinear systems with input constraints

“…This estimation allows for the compensation of unknown nonlinearity effects in the control input. (5) The necessary and sufficient conditions are provided for the optimality of the proposed approach and a stability and optimality analysis of the method is performed. The structure of this paper is as follows: Section 2 gives useful mathematical preliminaries and some assumptions.…”

“…Real-world applications of control systems have nonlinear dynamics that various control approaches are designed to guarantee their stability. This includes Lyapunov-based nonlinear control, adaptive control, and robust control methods [1][2][3][4][5][6][7][8]. In order to achieve other objectives rather than stability (e.g.…”