Abstract：To solve the problem of step response identification of low-order system with time delay, a parameter estimation method based on particle swarm optimization is proposed. The method consists of the calculation of initial parameters and the parameter estimation. Firstly, an integral equation approach is utilized to estimate the initial parameters of the system with time delay. By setting an initial parameter estimation error, the parameter range of the time-delay system can be determined. Next, the particle swarm optimization algorithm is employed to reduce the influence of the measurement noise on parameter estimation. Simulation experiments are conducted to verify the performance of the proposed method in identifying the parameters of low-order system with time delay under different noisy conditions. Experimental results demonstrate that the proposed method possesses good parameter estimation precision and strong anti-noise ability and it effectively solves the step response identification problem of low-order system with time delay.
李敏花, 柏猛, 吕英俊. 基于粒子群优化的低阶时滞系统辨识[J]. 模式识别与人工智能, 2019, 32(6): 524-530.
LI Minhua, BAI Meng, LÜ Yingjun. Identification of Low-Order System with Time Delay Based on Particle Swarm Optimization. , 2019, 32(6): 524-530.
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2019, Vol. 32 
