Adaptive Super-Twisting Sliding Mode Control for Nonlinear Dynamic Systems with Unknown Polynomial Perturbations

Abstract The study focuses on the control of nonlinear dynamic systems in the presence of parameter uncertainties, unmodeled dynamics, and external disturbances. The lumped perturbation is assumed to be bounded within a polynomial in the system state with the polynomial parameters and degrees unknown a priori such that it accommodates a quite wider range dynamic systems. Based on the analyses about the stability issues existed in recent super-twisting algorithm ( STA ) designs and the idea from adaptive sliding mode control ( ASMC ) for nonlinear systems with uncertainties, we propose a novel adaptive super-twisting algorithm with exponential reaching law, exponential super-twisting algorithm ( ESTA ), for the high-stability, chattering-free, and acceptable accuracy control of the aimed nonlinear dynamics. The stability analysis and finite-time convergence are proven using Lyapunov theory and an intuitive analysis of the control behaviour. Simulations are performed to compare the proposed ESTA with the existing STA method and the traditional proportional integral control. The simulation results demonstrate the effectiveness of the proposed ESTA in terms of the fastest settling time and the smallest overshoot.