Optimal control of the dynamic stability for robotic vehicles in rough terrain

In this paper, we mount semi-active suspensions between the wheels and platform of a robotic vehicle to absorb the vibrations caused by movement over rough terrain. The semi-active suspension consists of a spring and a magneto-rheological damper. By combining the dynamic model of the suspended robotic vehicle and the control model of the damper, we propose a new methodology to evaluate the dynamic stability of the vehicle. The model considers the configuration of semi-active suspensions and the road-holding ability of robotic vehicles. Based on the stability criterion, we use the particle swarm optimization method to search the optimum semi-active damping characteristics. The control model of the semi-active damper is checked by sinusoidal response analysis. To verify the dynamic stability criterion and the control method, we evaluate the proposed methodology by simulating a rough pavement condition and comparing the effectiveness of the method to a passive suspension. The results show that the proposed stability criterion is feasible, and the optimal control method yields a substantially improved dynamic stability when the vehicle moves through rough terrain.