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This paper develops an intelligent robust control algorithm for a class of uncertain nonlinear multivariable systems by using sliding model technology. The proposed control algorithm consists of an adaptive recurrent cerebellar model articulation controller (RCMAC) and a robust controller. The adaptive RCMAC is a main tracking controller utilized to mimic an ideal sliding mode controller, and the...
A design technique of a recurrent cerebellar model articulation controller (RCMAC)-based fault-tolerant control (FTC) system is investigated to rectify the nonlinear faults of a biped robot. The proposed RCMAC-based FTC (RCFTC) scheme contains two components: 1) an online fault estimation module based on an RCMAC is used to provide approximation information for any nonnominal behavior due to the system...
This paper addresses the problem of controlling unknown multiple-input-multiple-output nonlinear systems. First, a sliding mode controller for robust tracking control of multivariable nonlinear systems is developed. In case of unknown of system dynamics, an adaptive fuzzy sliding mode controller (AFSMC) is used to approximate the equivalent control with online self-tuning of fuzzy parameters. Secondly,...
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