Adaptive Fixed-Time Sliding-Mode Trajectory Tracking Control of a Cart-Pendulum Robot Against Actuator Attacks

This paper proffered an adaptive fixed-time sliding-mode control law to ensure that the cart-pendulum robot suffered by the actuator attacks of false-data injection moves along the reference trajectory. The neural network skill is availed to approach the nonlinear state-dependent actuator attack, and then a class of linear filter operators is used to collect the reckon deviation informations of the anonymous attack parameters, and an adaptive update law that can accurately identify the attack parameters within a fixed time is designed. Then a fixed-time control law is developed relying on adaptive integral sliding mode technology, which can adaptively offset the affect of actuator attack and accomplish the objective of tracking the reference trajectory. Using the Lyapunov stability theorem, it is verified the trajectory tracing error of the system merge to the residual set near zero in a fixed-time. Finally, the reliability of the devised control law is verified through the simulation case of the transporting mechanical arm.