| Summary: | 碩士 === 國立成功大學 === 造船及船舶機械工程學系 === 89 === In this study, an adaptive fuzzy-H∞ controller for multi-input multi-output nonlinear systems is proposed to improve the system tracking performance while maintaining the closed-loop system stability. In nonlinear systems, there are many nonlinear parameters, which generally are uncertain or unknown. To reduce the estimated error, some fuzzy-logics and an adaptive algorithm are utilized in this research to obtain the optimal parameters of the proposed controller. Furthermore, in order to guarantee the closed-loop stability and to ensure the system robustness against the external disturbances and uncertainties, an H∞-control law is included in the proposed composite control law. The H∞-controller can be attained by simply solving a Riccati equation via a recursive process to minimize the H∞-norm of the closed-loop transfer function between the exogenous inputs and the controlled outputs. Because the robot manipulators can be modeled as nonlinear multi-input multi-output systems, which have uncertain external loads and can also be applied as carrying equipments on ships’ desks, a robot manipulator is then simulated to demonstrate the feasibility of the proposed adaptive fuzzy-H∞ controller in this study. The simulation results reveal that if the weighting matrices in the controller are properly chosen, all the prescribed performances, including the reduction of the tracking errors, can be achieved even though the manipulator encounters plant uncertainties and external disturbances. Thus, the simulation results also show that the proposed controller law is robust to plant uncertainties and external disturbances.
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