Vibration control of an active vehicle suspension systems using optimized model-free fuzzy logic controller based on time delay estimation. (January 2019)

• Record Type: Journal Article
• Authors: Mustafa, Ghazally I.Y.; Wang, H.P.; Tian, Yang
• Is Part Of: Advances in engineering software. Volume 127(2019)
• Page Start: 141
• Page End: 149
• Publication Date: 2019-01
• Subjects: Active suspension system -- Model-free control -- Fuzzy logic control -- TDE -- PSO -- AMESim; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2018.04.009
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: This paper introduces a new optimized model-free FLC based on time delay estimation. The advantage of PSO-MFFLC is a quite simple structure and easily to be regulated. Nonlinear quarter car active suspension system model is proposed to validate the control approach. The control objective is to increase the ride comfort and the ride safety. A comparison with TDEC, classic PID, and iPID was conducted in Co-Simulation platform to demonstrate the effectiveness of the PSO-MFFLC. Abstract: This paper presents a new model-free fuzzy logic controller based on particle swarm optimization (PSO-MFFLC) for the nonlinear active suspension systems. The proposed method comprises the model-free based intelligent PID controller, the fuzzy logic controller, the time-delay estimation, and the particle swarm optimization. The advantage of PSO-MFFLC is quite simple structure and easy to be regulated. To validate the proposed controller, the nonlinear active suspension systems with non-linearity such as the parameters variation, external disturbance, and friction force effect are simultaneously taking into account to provide a realistic framework. The control objective is to deal with the classical conflict between minimizing vertical chassis acceleration to increase the ride comfort and keeping the dynamic wheel load small in order to ensure the ride safety. Moreover, modeling performed using a virtual detailed simulation environment LMS-AMESim, while the control part configured on Matlab/Simulink. Finally, the comparison of PSO-MFFLC with a classical PID, intelligent PID and the time-delay estimation control (TDEC) is conducted for different roads disturbances.