Design of fuzzy controller for dynamic positioning based on improved particle swarm algorithm

The traditional PID controller commonly used in ship dynamic positioning has the defects of difficult online adjustment and weak anti-interference ability. Combining fuzzy control with PID can be a good way to improve the adaptability and accuracy of the controller. However, the parameters of fuzzy PID need to be adjusted by human beings, and there exists a certain uncertainty, which has a great influence on the robustness of the controller. Therefore, the fuzzy PID is optimized using an improved particle swarm algorithm to parameterize the quantized scale factor and rules of the fuzzy PID. Particle swarm optimized fuzzy PID was simulated, and the control of PID and fuzzy PID controllers was compared under different operating conditions, as shown by the experimental results: Under the hydrostatic condition, the convergence speed of the control system is faster; under the load condition, the overshooting amount of the control system is smaller, and the robustness and adaptability have been significantly improved.