Disturbance-resistant path-tracking control method for robotic fish with tracking error constraints
To address the issue of low tracking efficiency of robot fish under disturbance,this study proposes an anti-disturbance and adaptive error constraint control scheme.Firstly,by designing a virtual control input and updating the adaptive line-of-sight guidance law using integral link,the motion position deviation caused by side slip is eliminated and the robot's anti-interference ability is enhanced.Secondly,by constructing an adaptive controller for yaw and surge of the robot fish,the neural network function fits uncertainties and flow disturbances in the model,compensating for system control input with an approximation value.This improves the body's adaptability to environmental conditions.Finally,utilizing obstacle Lyapunov theory,consistent final boundedness of robot fish tracking position and angle is proven.Through simulation and experiment,compared with the classical guidance scheme,the proposed scheme improves the tracking efficiency and steady-state performance of the robot fish,and the position error convergence rate of the robot fish is increased by 14.57% on average.
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