Optimal Control Method of Semi-Active Suspension System and Processor-in-the-Loop Verification
Source abstract
Abstract
This study presents an implementation of a proportional–integral–derivative (PID) controller utilizing particle swarm optimization (PSO) to enhance the compromise on road holding and ride comfort of a quarter car semi-active suspension system (SASS) through simulation and experimental study. The proposed controller is verified with a processor-in-the-loop (PIL) approach before real-time suspension tests. Using experimental data, the magnetorheological damper (MR) is modeled by an artificial neural network (ANN). A series of experiments are applied to the system for three distinct bump disturbances. The algorithm performance is evaluated by various key metrics, such as suspension deflection, sprung mass displacement, and sprung mass acceleration for simulation. The phase plane method is used to prove the stability of the system. The experimental results reveal that the proposed controller for the SASS significantly improves road holding and ride comfort simultaneously.
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Research context
OpenAlex topics: Vibration Control and Rheological Fluids · Hydraulic and Pneumatic Systems · Vehicle Dynamics and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Automotive Engineering, Faculty of Technology, Gazi University, 06500 Ankara, Türkiye
Department of Electrical-Electronic Engineering, Faculty of Technology, Gazi University, 06500 Ankara, Türkiye
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