Online High Performance Genetic Algorithm Based Sliding Mode Control for Controllable Pitch Propeller

Abstract

During the voyage of a ship, the performance of a controllable pitch propeller (CPP) is severely affected by the changing load demand and ever-present disturbance from ocean waves, which will also result in model uncertainty. In order to improve the performance of the CPP system, an online high-performance genetic algorithm (HPGA)-based sliding mode control (SMC) strategy is proposed. Firstly, the model of the CPP system is obtained according to the manufacturer’s instructions. Then, a chattering-free sliding mode controller (CF-SMC) is designed for the CPP system, after which the parameters in the CF-SMC are optimized with the HPGA method. Finally, the optimized CF-SMC is applied to an experimental setup of a prototype CPP system. In order to validate the effectiveness of the proposed method, it is compared with a proportional-integral-derivative (PID) controller, which is typically applied on real CPP-systems, with results indicating the superiority of the proposed method.