Intelligent modeling and control for nonlinear systems with rate-dependent hysteresis

• Published in: Science China. Information sciences Vol. 52; no. 4; pp. 656 - 673
• Main Authors: Mao, JianQin, Ding, HaiShan
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science in China Press 01.04.2009; Springer Nature B.V
• Subjects: Actuators; Adaptive control; Algorithms; Computer Science; Computer simulation; Controllers; Hysteresis; Information Systems and Communication Service; Learning; Magnetic properties; Magnetostriction; Modelling; Neural networks; Nonlinear control; Nonlinear systems; 控制器参数; 智能建模; 模糊树模型; 滞后非线性; 直接逆控制; 超磁致伸缩驱动器; 非线性系统; 频率依赖性; nonlinear systems with rate-dependent hysteresis; intelligent modeling and control; T-S fuzzy model; fuzzy tree model; adaptive inverse control
• DOI: 10.1007/s11432-009-0026-8
• ISSN: 1009-2757; 1674-733X

A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than the existed approaches. Compared with the experiment result, the model built can well describe the hysteresis nonlinear of the actuator for input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the fuzzy tree model and inverse learning and special learning that are used in neural network broadly. In this approach, the inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model is connected with the plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line manner. The direct inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator by simulation. The simulation results show the correctness of the approach.