Neural Network-based Adaptive Passive Output Feedback Control for MIMO Uncertain System

A neural network--based adaptive passive output feedback control problem is studied for a class of multi-input multi-output nonlinear systems with unknown nonlinearities and unknown parameters. Neural networks are used to identify unknown nonlinearities, and the update laws of weight parameters and constant parameters are proposed. The design methods of the adaptive passive controllers for this class of systems are discussed in the paper. The corresponding adaptive passive controllers and parametric adaptive laws are designed and presented respectively. It is proved that the closed-loop system composed of the original system and the designed controller is stable by the Lyapunov method, and the controller designed can render the closed system adaptive passive. Finally, a simulation example is given to prove the effectiveness and feasibility of the proposed method.