Tuning of Ship Heading Controller Based on Minimum Rate of Energy Dissipation and Multi-Attribute Decision Making Method

Abstract

The PID control is most widely used in industry and its parameters setting is an important issue in the field of automatic control. In this paper, a novel tuning strategy based on multi-objective genetic algorithm (MOGA) and multi-attribute decision-making (MADM) method was proposed. The proposed strategy can balance the four performances simultaneously regarding accurate set-point tracking, disturbance attenuation, robust stability and energy consumption for actuator. The estimated Pareto-optimal set was obtained by MOGA and then an appropriate solution was selected from the set by ranking with a simple additive weighting method (SAW). To demonstrate the proposed strategy, an example of the ship course PID controller with filter for a 150,000-ton tanker with steering gear was studied. The results show that the PID controller is stable and robust with high dynamic quality.