Ship attitude adaptive control algorithm considering multiple constraints
The ship's attitude is affected by complex nonlinear dynamics,such as hydrodynamic force,wind force,wave force and so on.These factors lead to the nonlinear and uncertain motion of the ship,which makes the precision of the attitude control of the ship low.Therefore,an adaptive attitude control algorithm considering multiple constraints is pro-posed.The low frequency and high frequency motion models of ships are constructed by analyzing their sailing on the sea.Obstacle avoidance constraints,minimum turning radius constraints and control input saturation constraints of ship naviga-tion are established according to the characteristics of ship navigation,and the objective Function of ship navigation attitude control is established to adjust the energy consumption at the least,and the objective function is approached by Radial Basis Function(RBF)neural network.The attitude control law of ship sailing which is close to the objective function is obtained,and the attitude adaptive control is completed.The experimental results show that this method can accurately control the ship's attitude,the output of the control quantity is close to the ideal state,the maximum static error is only 0.15°,and the control time and overshoot are small.
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