Observer-Based Adaptive Neural Control of Time-Delay Uncertain MIMO Nonlinear Systems

In this paper, observer-based adaptive neural control is proposed for a class of time-delay uncertain Multi-Input-Multi-Output (MIMO) nonlinear systems with input saturation. Function uncertainties, time-delay state function perturbations, unknown disturbances and input saturation are explicitly considered in the adaptive control design. The state observer is proposed to estimate unmeasured states and the adaptive tracking control is investigated to handle system uncertainties and external disturbances using neural networks (NNs) and parameter adaption method. For tackling the input saturation, an auxiliary design system is introduced to analyze the effect of input saturation, and states of auxiliary design system are used to develop the adaptive neural control. Under the proposed observer-based adaptive neural control, asymptotical stability of all closed-loop signals is obtained via Lyapunov analysis.