Research Of Fuzzy Sliding Mode Control Based On Quantum Genetic Algorithm For Full Vehicle Active Suspension

Suspension is one of the important components of vehicle chassis system, which is used for passing the force and moment between the car body and tires, alleviating the impact load caused by the rough road and guaranteeing the ride comfort and stability in the process of driving the car. Nowadays the majority of the cars equip the passive suspension system. This form of damping devices is unable to meet the requirements of ride comfort for passengers because of its fixed damping coefficient and spring stiffness coefficient for the complex road conditions. Active suspension technology control the suspension actuators to adjust the body posture in real time according to the road excitation and body condition through external energy and intelligent control strategy. This technology is useful to improve the ride comfort, thus it gradually gets the attention of people.This paper researched on the simulation of control strategy and the road test for home-made experimental vehicle with active suspension, which was based on the special fund project for automobile industry development in Jilin province: Research and Development for Active Suspension with Inertia Control(Project No. 20112330). The specific research work are as follows.(1) Set up the vehicle suspension system model and road model. This paper simplified the model of home-made experimental vehicle with active suspension, and established the mathematical model of 7 degrees of freedom and the ideal reference model with skyhook dampers. An error dynamics model about the controlled system and reference model was also built. A random road input model was built in consideration of the controller design and simulation analysis, as well as the performance evaluation index for vehicle.(2) Design the fuzzy sliding mode controller based on quantum genetic algorithm. A fuzzy sliding mode controller using modular control thought was built to track the ideal reference model. Fuzzy logic theory was used to optimize the gain coefficient of reaching law in the sliding mode controller. This paper used quantum genetic algorithm to optimize the fuzzy rules of fuzzy controller at the same time.(3) The simulation analysis of vehicle active suspension system. Matlab/Simulink was used to simulate and analysis the riding comfort and stability of vehicle with passive suspension and active suspension. The simulation results show that effect of active suspension controller with fuzzy sliding mode control strategy based on quantum genetic algorithm is remarkable in the inhibition of vehicle vibration and improvement of ride comfort, comparing with the passive suspension system. At the same time, the vehicle active suspension controller has strong robustness for system parameters perturbation.(4) Road test for the home-made experimental vehicle. In order to test the simulate effect of controllers, road tests of home-made experimental vehicle with different active suspension controllers were conducted. Test results show that the root mean square for acceleration of the vehicle body’s vertical vibration, pitch angle and roll angle with active suspension decrease by 42.28%, 39.84%, 39.44%, compared with the one based on passive suspension. The use of active suspension system can improve the vehicle riding comfort.The study show that effect of active suspension with fuzzy sliding mode control based on quantum genetic algorithm is effective. The active suspension system can significantly improve vehicle’s dynamic performance, which has important research significance and practical value.