Design Of Ship Course Autopilot In The Presence Of Input Saturation

The theory of ship course autopilot is applied earlier and has achieved remarkable results in the field of automatic control. In recent years, there has a growth of research efforts aiming at the control algorithm of systems with input saturation, but few results are found in ship autopilot design.In this paper, three novel control algorithms are proposed for ship course autopilot with rudder angle limitation, and three conditions of systems with known certainty, parameter uncertainty and arbitrarily uncertainty are considered, respectively.First, with the help of an auxiliary system, a novel ship course controller is proposed for ship course control system with input saturation, and it shows that relatively high effectiveness and good performance. Second, combining Lyapunov theorem with the Backstepping technique, a robust adaptive control algorithm is proposed for the ship course autopilot with parameter uncertainties and input saturation and unknown external disturbance. Third, considering the system with arbitrarily uncertainty and input saturation and unknown external disturbance, a neural network-based direct adaptive dynamic surface control (DSC) scheme is developed by using neural network as an approximation for the arbitrarily uncertainty. And it is applied to ship course autopilot control design.DSC is introduced for solving the problem of "explosion of complexity" which is inherent in the conventional backstepping technique, and it is convenient to implement in applications. In addition, by utilizing a special property of the affine term and the direct adaptive control, the proposed scheme avoids the controller singularity problem.The proposed algorithms can guarantee the stability of the closed-loop system, and make the tracking error arbitrarily small. Finally, MATLAB simulation results are used to demonstrate the effectiveness of the proposed scheme.