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提出了一种采用粒子群算法优化多模型控制器参数的直流炉燃水比解耦控制方法。在种群初始化、惯性权值和变异率引入方面对基本粒子群算法进行了改进,以提高算法的收敛精度和速度。对解耦后的系统,分别用改进粒子群算法、基本粒子群算法和工程整定法得到了控制器参数,完成了燃水比控制的仿真试验。结果表明,使用基于改进粒子群算法的控制策略的系统较传统控制策略下的系统动、静态特性更好,更能适应深度调峰的需要。
A DC / DC ratio decoupling control method based on Particle Swarm Optimization (PSO) is proposed to optimize multi-model controller parameters. The PSO algorithm is improved in terms of population initialization, inertia weight and mutation rate, in order to improve the convergence accuracy and speed of the algorithm. For the decoupled system, controller parameters are obtained by using improved particle swarm optimization algorithm, basic particle swarm optimization algorithm and engineering tuning method, respectively. The simulation experiment of fuel-water ratio control is completed. The results show that the system using the control strategy based on the improved particle swarm optimization is better than the traditional control strategy in terms of system dynamic and static characteristics and can better meet the requirements of peak shaving.