Adaptive Iterative Learning Control for Systems with Nonlinearities
In this paper we consider the problem of ILC when it deals with systems with piecewise linear nonlinearities. Most of actuators have nonlinear characteristics such as hystersis, backlash, deadzone or piecewise linear nonlinearities. These nonlinearities make controller design difficult, specifically when their parameters are not known. Iterative learning control, (ILC), uses an iterative algorithm to track a fixed reference output signal in a specific period of time. We use the results of iterative learning control design based on 2D system theory and nonlinearity inverse method to compensate the effect of the actuator nonlinearity.
Iterative learning control Piecewise linear nonlinearity nonlinearity inverse method 2D system theory
Iman Khademi Masoud Shafiee
Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
29-34
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）