Adaptive Neuro-Sliding Mode Control for Multivariable Nonlinear Systems with State Observer

摘要

In this work, a stable adaptive neural sliding mode controller is developed for a class of multivariable uncertain nonlinear systems. For these systems not all state variables are available for measurements. By designing a state observer, adaptive neural systems, which are used to model unknown functions, can be constructed using the state estimations. The designing of the adaptive neuro-sliding mode controller is combined neural systems and sliding mode control technique, and based on Lyapunov stability theorem, the stability of the whole closed-loop system is rigorously proved. Adaptive laws are proposed to adjust the free parameters of the neural models. Simulations performed an a two-link robot manipulator illustrate the approach and exhibit its performance.