A control method for water cannon of unmanned fireboats based on EGWO-ADFUZZY

In order to improve the accuracy and efficiency of marine firefighting operations, a control method for firefighting water cannon of unmanned fireboats based on EGWO-ADFUZZY is proposed in this paper. Firstly, the improved enhanced grey wolf optimization (EGWO) algorithm is used in conjunction with the jet trajectory model to design the EGWO main controller. Based on this controller, search range adjustment strategy and jet trajectory model correction strategy are proposed. Secondly, the online particle swarm optimization (PSO) algorithm is integrated with the fuzzy control algorithm to enhance its adaptive capability. As a result, the adaptive fuzzy (ADFUZZY) controller is designed to cope with ship motion disturbances. The experimental results show that, the EGWO-ADFUZZY controller can quickly perform firefighting operations within an error range of 5 x 10-2 m. Compared to the double adaptive fuzzy control method, it exhibits an efficiency improvement of approximately 40%. Furthermore, it further confirms that this method is capable of effectively countering the disturbances caused by ship motion, ensuring the efficiency of firefighting operations for unmanned fireboats at sea. This control method provides valuable insights and references for future research and engineering applications in marine firefighting.