Observer-Based Adaptive Fuzzy Robust Controller with Self-Adjusted Membership Functions for a Class of Uncertain MIMO Nonlinear Systems: A PSO-SA Method
Source: National Cheng Kung University
In this paper, a novel adaptive fuzzy robust controller with a state observer approach based on the hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA) technique for a class of Multi-Input Multi-Output (MIMO) nonlinear systems with disturbances is proposed. The Particle Swarm Optimization-Simulated Annealing (PSO-SA) is used to adjust the fuzzy membership functions, while adaptive laws are used to approximate nonlinear functions and the unknown upper bounds of disturbances, respectively. A state observer is applied for estimating all states which are not available for measurement in the system. By using the Strictly-Positive-Real (SPR) stability theorem, the proposed adaptive fuzzy robust controller not only guarantees the stability of a class of MIMO nonlinear systems, but also maintains good tracking performance.