Adaptive Fuzzy Control For Nonlinear Systems With Unmodeled Dynamics

This thesis investigates the adaptive fuzzy control methods for multiple-input and multiple-output(MIMO)nonlinear system with unmodeled dynamics.For MIMO nonlinear systems with unmodeled dynamics,and MIMO nonlinear interconnected systems with unmodeled dynamics and input dead-zones,we design two different control schemes,i.e.,adaptive fuzzy control and adaptive fuzzy decentralized control,respectively.Based on the Lyapunov theory,the proposed control schemes ensure the expected control performance of the closed-loop system.The effectiveness of the proposed control schemes are verified by the simulation results.The compendious frame and description of this thesis are shown from the following two parts:1.For a class of MIMO nonlinear systems with unmodeled dynamics,a fuzzy adaptive control approach is studied.Fuzzy logic systems are used to approximate the unknown nonlinear systems,backstepping and adaptive control are combined to design controller.The proposed control scheme guarantees that all signals of the closed-loop systems are semi-globally uniformly ultimately bounded.Simulation results are used to further demonstrate the effectiveness of the proposed control scheme.2.An adaptive fuzzy decentralized control method is considered for a calss of MIMO nonlinear systems with unmodeled dynamics and input dead-zone.First,for the dead-zone nonlinearity,equivalent decomposition method is used to divide the dead-zone into the linear part of dead-zone input and a bounded perturbed part.Then,based on backstepping technique and fuzzy control method,an adaptive fuzzy decentralized control scheme without depending on the information of unsmooth nonlinear parameters is proposed.Finally,simulation studies further illustrate the effectiveness of the proposed control scheme.