ANFIS-Based Course Controller Using MMG Maneuvering Model

In the domain of course control, traditional methods such as proportional–integral–derivative (PID) control often exhibit limitations when addressing complex nonlinear systems and uncertain disturbances. To mitigate these challenges, the adaptive neuro-fuzzy inference system (ANFIS) has been integrated into course control strategies. The primary objective of this study is to investigate the course control characteristics of vessels governed by the ANFIS controller under both normal and severe sea conditions. A three-degree-of-freedom (3-DOF) maneuvering model set (MMG) was employed and validated through sea turning tests. The design of the ANFIS controller involved a combination of the backpropagation algorithm with the least square method. Training data for the ANFIS control system were derived from a linear control framework, followed by simulation tests conducted under normal and severe sea conditions to assess control performance. The simulation results indicate that in normal sea conditions, ANFIS has more stable heading control (smaller Aψ), but at the cost of more energy consumption (larger Iδ). Notably, response time is reduced by approximately 36.7% compared to that of the linear controller. Conversely, during severe sea conditions, ANFIS exhibits an increase in response time by about 33.3% relative to the linear controller while maintaining a smaller Iδ. In the whole course control stage, the stability is better than the linear controller, and it has better energy-saving characteristics. Under scenarios involving small and large course alterations, Aψ values for ANFIS are approximately 11.28% and 13.97% higher than those observed with the best-performing linear controller (λψ = 60), respectively. As the propeller speed increases, the Aψ value of the ANFIS controller decreases significantly, to about 62.71%, indicating that the energy efficiency is improved and the course stability is also enhanced. In conclusion, it can be asserted that the implementation of an ANFIS controller yields commendable performance in terms of controlling vessel courses effectively.