Research On Particle Swarm Optimized Fractional-order Controller And Its Application To Course Control For Underactuated Surface Vessels

Ship dynamics has the characteristics of large inertia, large time lag and high nonlinearity. And it is also affected by the factors such as the navigation condition, the change of cargo loading capacity, the moment of inertia and the change of gravity coordinates which make the parameters of the ship motion mathematical model change and lead to the uncertainty of the ship model. At the same time, the wind, wave and current are also taken as the parameters changing of the ship model. So the conventional linear and nonlinear control method is difficult to achieve the ideal control effect.The USV mainly uses rudder system to change or keep the ship's course, uses propeller thrust to change or keep the ship's velocity. So the rudder system effects propeller thrust each other.In this paper, it is introduced about fractional-order control of USV course-controlling based on particle swarm optimization algorithm, and the main contributions of the paper are as follows:Firstly, according to motion control of USV with the uncertainty of model parameters and the disturbance of outside environment, a fractional-order PI?D? controller is proposed in this paper and applied to the autopilot design of ship course control of USV. The simulation results show that the fractional-order PI?D? controller can improve the control precision and anti-disturbance ability of the ship's course, compared with the conventional PID ship autopilot.Secondly, because two additional adjustable parameters of integral-order ? and differential-order ?, make the fractional-order PI?D? controller more flexible, the particle swarm optimization algorithm is introduced into the design of the controller, and the parameters of the fractional-order PI?D? controller are adjusted online in this paper.The simulation results show that the fractional-order PI?D? controller based on PSO algorithm is effective in the course control of USV.Thirdly, because the inertia weight ? and maximum flight speed Vmax influence on the global searching ability and the local development ability of PSO algorithm, as well as their inner link. A time-varying nonlinear trigonometric function is proposed to improve the PSO algorithm in this paper and the improved PSO (IPSO) algorithm is applied to the parameter tuning of the fractional-order PI?D? controller of ship course. The simulation results show that the fractional-order PI?D? controller based on IPSO algorithm is effective in the course control of USV.Fourthly, according to the effect of learning factors c, and c2 on the search speed of the particle in the solution space, a new improved PSO algorithm based on asynchronous time varying learning factor is proposed in this paper. Two learning factors differently vary with time in the process of algorithm optimization. The IPSO algorithm is applied to the parameter tuning of the fractional-order PI?D? controller of ship course. The simulation results show that the fractional-order PI?D? controller based on IPSO algorithm is effective in the course control of USV.Fifthly, because the inertia weight influences on the global searching ability and the local development ability of PSO algorithm, a nonlinear dynamic inertia weight is proposed to improve the PSO algorithm in this paper and the IPSO algorithm is applied to the parameter tuning of the fractional-order PI?D? controller of ship course. The simulation results show that the fractional-order PI?D? controller based on IPSO algorithm is effective in the course control of USV.Finally, according to the advantages and disadvantages of particle swarm optimization algorithm, genetic algorithm (GA) and simulated annealing (SA) algorithm, the hybrid GA-PSO algorithm and improved SA-PSO algorithm are proposed in this paper. They can overcome the algorithm is easy to fall into local extremum, premature convergence or stagnation, and improve the global search ability and local search ability of the algorithm. The two kind hybrid PSO algorithms are applied to the parameter tuning of the fractional-order PI?D? controller of ship course. The simulation results show that the fractional-order PI?D? controller based on IPSO algorithm is effective in the course control of USV.