Speed Tracking Control for Unmanned Driving Robot Vehicle Based on Fuzzy Adaptive Sliding Mode Control

To achieve accuracy and stable speed tracking under different conditions, a speed tracking method for the unmanned driving robot vehicle with sliding mode gains adjusted by a fuzzy adaptive system is proposed. Using the complex vector method and equivalent substitution method, kinematics and dynamics models of driving mechanical legs are established. Combined with models of driving and brake systems of manipulated vehicles, the longitudinal dynamics model is built. Then the longitudinal manipulation strategy is established. Based on the dynamics model of the mechanical leg, the sliding mode controller's control law is deduced. In addition, the fuzzy adaptive approximation is constructed and the fuzzy adaptive law is designed. Furthermore, the stability of the fuzzy sliding mode controller is proven using the Lyapunov function. Finally, through simulation and experiment, a comparison among the proposed method and several existing control methods demonstrates the effectiveness of the proposed method.

Automated summary

This paper proposes a speed tracking method for unmanned driving robot vehicles by adjusting the sliding mode gains using a fuzzy adaptive system. The effectiveness and stability of the proposed method is demonstrated through model establishment and control law derivation.