Optimization Control System using the Quantum Behaved Particle Swarm Optimization on Vehicle Steering Control System with Steer-by-Wire System

Abstract

Fuzzy Logic includes a technique are widely applied to the vehicle steering control system, however, to get the parameters required by a reliable Fuzzy Logic Control (FLC), needed training and learning process. Quantum behaved Particle Swarm Optimization (QPSO) is a simple optimization method that guarantees the achievement of global convergence quickly. This paper aimed to optimize of the steering control system on vehicle with steer-by-wire system using QPSO. The vehicle steering control system consists of Fuzzy Logic Control (FLC) and the Proportional, Integral and Derivative (PID) control are built in cascade, in which FLC is used to minimize the lateral motion error and PID control is used to suppress yaw motion error of the vehicle. The parameters of the control system are optimized by QPSO consists of three parameters to determine the position of the centre and the width of the triangle membership function of FLC and three constant gain of PID control. The optimization is done through the software in the loop simulation of vehicle models represented by 10 Degree of Freedom (DOF) of the vehicle dynamics. Simulation results showed that optimization using QPSO on the parameters of the control system can guarantee the movement of the vehicle is constantly maintained at the desired trajectory with a smaller error and higher vehicle speeds compared to the control system without tuned. The results obtained will be used as the basis for testing of the hardware in the loop simulation (HILS) so it can further improve the performance of steer-by-wire system.