Adaptive inverse control of discrete system using online PSO-IIR filters

作者：Liu Jianchang^*; Yu Xia; Li Hongru

来源：Journal of Computational Information Systems, 2010, 6(10): 3173-3182.

• Adaptive IIR filters
• Adaptive inertia
• Adaptive inverse
• Adaptive inverse control
• Computing cost
• Control objectives
• Convergence speed
• Discrete systems
• Filter weights
• Inertia weight
• Inverse controllers
• On-line system identification
• Particle swarm optimization algorithm
• PSO algorithm
• Simulation result
• Training sequences

Traditional adaptive inverse control systems are often used FIR filters, such filters will make the system costing increasing as long training sequence is needed and the slow convergence occurs at the same time. Thus, it is unable to adapt the requirements of the real-time control systems. In this paper, an IIR filter is designed using an improved adaptive inertia weight particle swarm optimization (PSO) algorithm to reduce the computing costs and improve the convergence speed of the filter weight. Also, this PSO-IIR filter is used in discrete adaptive inverse system for online system identification and online inverse controller adjusting. Simulation results show that, for discrete uncertain systems, this method can make the system achieve control objectives quickly and effectively.

• 出版日期2010
• 单位东北大学