Obstacle avoidance and MPC trajectory tracking of unmanned surface vehicle formation based on improved DWA
A self-following dual-mode obstacle avoidance mod-el predictive control method based on improved dynamic win-dow method was proposed for the trajectory tracking control problem of unmanned surface vehicle(USV)formation under the influence of sudden obstacles.Firstly,the longitudinal ve-locity and bow angular velocity oscillation constraints were in-troduced to reduce the jitter of the velocity and bow angle in the design of the evaluation function of the dynamic window algorithm so as to achieve better integration of obstacle avoid-ance planning and control.A strategy of calculating the steer-ing azimuth based on intermediate distance was proposed to reduce the sharp turns in the obstacle avoidance process of the USV,while an evaluation term based on the deviation of the predicted and the expected position ending was designed.Meanwhile,the formation keeping information was combined to correct the obstacle avoidance endpoint and reduce the de-viation of the USV formation.Secondly,based on the linear-ized Taylor expansion principle,a prediction model for USV formation was designed.The prediction value of the model was corrected by the prediction error between the system output measurement and the model prediction values.At the same time,a rolling finite time domain iterative online optimization strategy was adopted to propose a trajectory tracking model prediction control method for USV formation that integrated autonomous following dual-mode obstacle avoidance strategy.Finally,a nonlinear disturbance observer was designed to compensate the environmental disturbances,while the Lya-punov function was constructed to prove the stability of the system by combining with the terminal penalty theory.Eventu-ally,the effectiveness and reliability of the proposed USV for-mation obstacle avoidance and trajectory tracking control algo-rithm were verified by simulation experiments.
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