Design of Fuzzy Super Twisting Sliding Mode Control Scheme for Unknown Full Vehicle Active Suspension Systems Using an Artificial Bee Colony Optimization Algorithm

Abstract

AbstractThis article proposes a new intelligent control scheme that uses the Fuzzy Super Twisting Sliding Mode Concept (FSTSMC) and PID controller tuned with the Artificial Bee Colony (ABC) algorithm to control a full vehicle active suspension system with new convergence proof. Suspension systems are utilized to provide vehicle safety and improve comfortable driving. The effects of road roughness transmitted by tires to the vehicle body can be reduced by using suspension systems. In this work super twisting sliding mode is combined with a fuzzy system to design a robust control method. The super twisting sliding mode concept is utilized to limit and minimize the chattering problem and the fuzzy system is used for estimating the unknown parameters and uncertainty in the suspension system components (spring, damper, and actuator). The advantage of such combination is that it can handle the uncertainties and nonlinearities efficiently. The PID controller is used to create the required force to be produced by the actuator. The proposed control scheme consists of four similar sub control schemes, one for each of the four corners of the vehicle. All parameters in the sub control schemes are optimized using the ABC algorithm. The designed control system is applied for a full vehicle model with 8 degrees of freedom. Simulation results show large reduction in the vibration of the vehicle body when passing on disturbance and also show good robustness properties when tested for different road conditions. Passive and active suspension systems using sliding modecontrol (SMC) and the proposed FSTSMC are compared to test the efficiency and the ability of the proposed control scheme to achieve safe and comfortable driving for a random road profile.