Adaptive control of large transport ship based on grasshopper optimization algorithm

  Objectives  The maritime navigation environment is random, complex and changeable, and intelligent autonomous navigation is an important trend in the development of large ocean-going transport ships, for which a new adaptive control method is proposed.

  Methods  First, the linear quadratic regulator (LQR) control method is integrated with the first-order dynamic integral sliding mode control method based on the grasshopper optimization algorithm (GOA). A nonlinear passive estimator with real-time monitoring of wave disturbance forces is then combined to separate the high and low-frequency motion signals of the ship. Finally, the simulation results of the proposed method are compared with those of the LQR control method and first-order dynamic integral sliding mode control method.

  Results  The results show that the new control method has better transient and steady-state tracking performance, and is able to overcome the effects of random waves under different sea conditions with strong robustness.

  Conclusions  The new control method has such abilities as self-adjustment in complex environments, fast control response, high precision and less redundant steering, enabling it to greatly improve the navigation efficiency, safety and stability of large transport ships.