Fault-Tolerant Trajectory Tracking Based on Improved Chaotic Firefly Algorithm Model Prediction Control for Human-Occupied Vehicle With Ocean Current

Abstract

In this article, aiming at the characteristics of model uncertainty and low-speed of human-occupied vehicle (HOV) system, a cascaded controller in ocean current environment is proposed. First, the kinematics controller is designed by improved chaotic firefly algorithm (ICFA)-model predictive control (MPC) to get the speed control signal. The multivariable constraint capability of ICFA-MPC can solve the problem of speed jump caused by thruster fault and further solve the problem of driving saturation. Second, the kinematic controller is combined with the dynamics controller which is according to the adaptive algorithm. The adjustable control parameters capability of the adaptive control can further obtain the dynamic control law under the influence of ocean current. Finally, the hybrid allocation strategy based on ICFA is used to redistribute the thruster force/moments. Simulation results displayed the dynamic trajectory tracking fault-tolerant controller can steadily track the reference trajectory under thruster fault without tracking disturbance, speed jump, and driving saturation problem.