Modified Grey Fuzzy Logic Controller for Vehicle Suspension System
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This paper presents a Modified Grey Fuzzy Logic controller for enhancing the ride comfort and road holding ability of Vehicle Suspension System (VSS) simultaneously. Grey Prediction algorithm is used to pre-compensate the error. The prediction error in Grey Model (GM) is minimized by changing the initial condition and optimizing the weight factor in the data matrix of grey prediction algorithm. The aim of this paper is to design two Traditional Fuzzy Logic Controllers (TFLC), one for minimizing the sprung mass displacement error and the other for tyre deflection error. TFLC uses the grey model to design Grey Fuzzy Logic Controller based VSS. Particle Swarm Optimization (PSO) is used to optimize the weighting factor of grey model. The proposed controller is simulated for a Quarter Car model of VSS. Simulation results show that the proposed controller enhances both ride comfort and road holding ability simultaneously
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