【摘要】 针对基本PSO算法本身存在着的对于离散的优化问题处理不佳,以及容易陷入局部最优等缺点,设计了一种引入线性递减权重机制与模拟退火算法(SA)思想的改进粒子群算法(SA-PSO),并将SA-PSO算法应用到火电厂主汽温控制系统的PID控制器参数整定中。MATLAB仿真实验结果表明:在62%,88%及100%3种不同负荷的工况下进行控制系统参数优化时,SA-PSO算法与基本PSO算法及传统Ziegler-Nichols参数整定法(Z-N法)相比,更加不容易陷入局部最优,提高了主汽温控制系统的控制品质。仿真实验的结果证明了SA-PSO算法的有效性以及在实际工业状况下的适用性。更多还原

【Abstract】 Aiming at the shortcomings of the basic PSO algorithm,such as poor performance of discrete optimization and local optimum trap,an improved particle swarm optimization algorithm(SA) with linear decreasing weight mechanism and simulated annealing algorithm(SA-PSO) is designed.The improved SA-PSO is applied to the PID controller parameter tuning of the main steam temperature control system of the thermal power plant.The simulation results via MATLAB show that the controller tuned by proposed SA-PSO algorithm has higher immunity to the local optimum trap comparing to the basic PSO algorithm and the traditional Ziegler-Nichols parameter tuning method(Z-N method) working under the load conditions of 62%,88% and 100% respectively,which proves that the quality of the control is increased.The simulation results demonstrate the effectiveness of the SA-PSO algorithm and its applicability under actual industrial conditions.更多还原