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传统减摇鳍PID控制器的参数是根据特定海情选取的,不具有自整定的能力。当海情变化以后,由于船舶横摇数学模型的非线性,往往造成减摇效果变差。微粒群算法(PSO)作为一种群体智能优化算法,具有输入参数较少、收敛速度快的特点。以船舶减摇鳍控制系统作为对象,为了实现了减摇鳍PID控制器参数的自整定,提出一种基于PSO算法参数自整定的减摇鳍PID控制器,并在不同海情下进行了仿真。仿真结果表明,与传统PID控制器相比,基于PSO算法参数自整定的减摇鳍PID控制器具有更好的控制效果。
Traditional fin stabilizer PID controller parameters are selected according to the particular sea conditions, do not have the ability to self-tuning. When the sea conditions change, the swaying effect often deteriorates due to the nonlinearity of the mathematical model of ship rolling. Particle Swarm Optimization (PSO), as a swarm intelligence optimization algorithm, has the advantages of less input parameters and faster convergence rate. Taking the fin stabilizer control system of the ship as an object, in order to realize the self-tuning of the parameters of the fin stabilizer PID controller, a self-tuning stabilizer PID controller based on the PSO algorithm is proposed and simulated under different sea conditions . The simulation results show that compared with the traditional PID controller, the PID controller based on PSO self-tuning fin stabilizer has better control effect.