Multi-agent chaos particle swarm optimization algorithm of thrust allocation for dynamic positioning vessels

As an important component of the vessel's Dynamic Positioning (DP) System, thrust allocation determines the control input of each thruster device from the control law. Thrust allocation problems can be formulated as nonlinear optimization problems. A chaos Particle Swarm Optimization (PSO) algorithm combined with multi-agent scheme is proposed for the thrust allocation in this paper. The algorithm which uses multi-agent topological structure has three functions that keeps the diversity of the particle swarm population, improving particle swarm global search ability, and enhancing information diversity. Relying on chaotic local search to get rid of local optima, it can also improve the convergence precision. The numerical simulations are conducted to demonstrate the effectiveness of the proposed methods, and the results are compared with PSO algorithm.