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Novel fuzzy sliding controller for MRD suspensions subjected to uncertainty and disturbance


Sy Dzung Nguyen, Huu-Vinh Ho, Thoi-Trung Nguyen, Nang Toan Truong, Tae-Il Seo

Source title: 
Engineering Applications of Artificial Intelligence, 61: 65-76, 2017 (ISI)
Academic year of acceptance: 

In this paper, the design of an adaptive optimal fuzzy sliding controller (AOFSC) for semi-active magnetorheological damper (MRD) vehicle suspension system subjected to uncertainty and disturbance (UAD) whose time-varying rate may be high but bounded is presented. This is a combination of an adaptive optimal fuzzy sliding mode controller (FSMCop), a nonlinear disturbance observer (NDO) and an inverse MRD model to create the desired control force, including the compensation part for UAD. An adaptive control law is proposed to establish a fuzzy-gain update law for the AOFSC and a parameter tie for the NDO such that the convergence of system's dynamic response is a Lyapunov asymptotically stable process. Surveys via simulations along with via an experimental apparatus showed that the high capability to exterminate vibration, robust stability, and the economic efficiency are the main advantages of the proposed AOFSC.