Disturbance event triggered-model predictive tracking control for 4WIS–4WID mobile robot

Wheel-ground interactions during operation cause the robot to deviate from the reference trajectory, affecting the stability and safety of the robot. An event-triggered model predictive control based on the observation disturbance triggering mechanism is proposed for the four-wheel independent steering and four-wheel independent driving wheeled mobile robot to handle this issue. The discrete error model is established based on the kinematic model, and its prediction model is further developed. During the robot’s movement, a discrete-time disturbance observer is used to estimate the bounded disturbances suffered by the robot. Then, a rolling optimization method based on the triggering mechanism of disturbance observation is proposed. By setting the disturbance threshold to determine if the optimal control problem should be solving within the sampling period, the optimization frequency of model prediction controller is reduced, which in turn saves computational resource consumption. Through simulation, it has been demonstrated that the controller design significantly decreases the robot’s computational resource consumption while tracking trajectories.