Heading MFA control for unmanned surface vehicle with angular velocity guidance. (November 2018) - Li, Ye; Wang, Leifeng; Liao, Yulei; Jiang, Quanquan; Pan, Kaiwen
Highlights: The angular velocity guidance part improves the dynamic performance including overshoot and oscillation of MFA method. The control-oriented adaptive Kalman filter is proposed which is independent of the mathematical model. The proposed adaptive Kalman filter suppresses the heading sensor noise well with stochastic model parameter perturbation. The improved MFA method has strong robustness and adaptability with uncertainties. Abstract: Based on the model-free adaptive control (MFA) theory, the heading control problem of unmanned surface vehicle (USV) with uncertainties is studied. The compact form dynamic linearization based MFA (CFDL-MFA) control method and its difficulties in USV heading control applications are analyzed. Aiming at the time delay of rudder-heading control system and the overshoot characteristic of CFDL-MFA method, the angular velocity guidance algorithm is introduced. The outer loop PID guidance controller calculates the desired angular velocity, and the inner loop MFA controller is used for angular velocity control. The heading control is realized indirectly. Considering sensor noise in applications, a control-oriented adaptive Kalman filter (AKF) based on dynamic linearized model is proposed, which effectively suppresses the adverse effect of sensor noise on heading control of USV. Numerical simulations of filtering experiments and heading control experiments are completed which demonstrate the validity of the proposed heading MFA control method with angular velocity guidance and the proposed AKF method.