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Second-Order Sliding Mode Controller for Performance Analysis of Quarter Car Magnetorheological Suspension System
Technical Paper
2020-01-1005
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
To achieve the simultaneous improvement in ride comfort of the passenger as well as the stability of the vehicle, a second-order sliding mode controller is proposed in this study. Super twisting algorithm attenuates the chattering effect present in the conventional sliding mode controller without affecting the stability of the system. The Lyapunov stability analysis is carried out to verify the stability of the controller. The effectiveness of the designed super twisting algorithm used second-order sliding mode controller is validated in a semiactive quarter car suspension with seat model. Modified Bouc-wen magnetorheological (MR) damper model is used as a semiactive damper and the voltage that has to be supplied to the magnetorheological damper is controlled by a super twisting algorithm and sliding mode controller. Continuous modulation filtering algorithm is adopted to convert the force signal of a controller into the equivalent voltage input to the MR damper. The entire system is modelled in Matlab/Simulink software and the simulations are carried out based on random road disturbances. The results show that there is a significant improvement in the second-order sliding mode controller semiactive MR suspension system compared with an uncontrolled passive suspension system. The robustness of the system is verified by analyzing it with mass uncertainties. Selected second-order sliding mode controller is validated by comparing it with a conventional sliding mode controller. The results depict a significant improvement in the performance of suspension system because of the application of the super twisting algorithm, second-order sliding mode controller.
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Soosairaj, A. and K, A., "Second-Order Sliding Mode Controller for Performance Analysis of Quarter Car Magnetorheological Suspension System," SAE Technical Paper 2020-01-1005, 2020, https://doi.org/10.4271/2020-01-1005.Data Sets - Support Documents
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