摘要
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。
The selection of the parameters of PID controller for the conventional fin stabilizer is based on the certain condition of the sea, so that the parameters of PID controller don't have the ability of self-adjusting. The effect of fin stabilizer often becomes worse when the condition of the sea changes, because of nonlinear mathematical model of the ship roll. As a kind of swarm intelligent optimization algorithm, particle swarm optimization(PSO) has the characteristics of less input parameters and fast convergence speed. Taken the ship fin stabilizer control system as an object, in order to fulfill the self-adjusting of PID parameters of the fin stabilizer controller, a kind of parameter self-adjusting fin stabilizer PID controller based on PSO algorithm is proposed, and is simulated in different conditions of the sea. The simulation results show that compared with the conventional PID controller, the fin stabilizer PID controller based on PSO algorithm has better control effect.
出处
《控制工程》
CSCD
北大核心
2016年第8期1197-1202,共6页
Control Engineering of China
基金
国家自然科学基金项目(512790359)
