Iterative learning control for linear time-variant discrete systems based on 2-D system theory - Control Theory and Applications, IEE Proceedings-

نویسنده

  • X.-D. Li
چکیده

The two-dimensional (2-D) system theory iterative learning control (ILC) techniques for linear time-invariant discrete systems are extended to the cases of linear time-variant discrete systems. By exploiting the convergent property of 2-D linear time-variant discrete systems with only one independent variable, a kind of 2-D system theory ILC approach is presented for linear time-variant discrete systems. Sufficient conditions are given for convergence of the proposed ILC rules. Two numerical examples are used to validate the ILC procedures.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Iterative Learning Control Method for Continuous-Time Systems Based on 2-D System Theory

This letter presents a two-dimensional (2-D) system theory based iterative learning control (ILC) method for linear continuous-time multivariable systems. We demonstrate that a 2-D continuous-discrete model can be successfully applied to describe both the dynamics of the control system and the behavior of the learning process. We successfully exploited the 2-D continuous-discrete Roesser’s line...

متن کامل

Iterative learning identification and control for dynamic systems described by NARMAX model

A new iterative learning controller is proposed for a general unknown discrete time-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification ar...

متن کامل

2-D Analysis for Iterative Learning Controller for Discrete-Time Systems With Variable Initial Conditions

In this paper, an iterative learning controller applying to linear discrete-time multivariable systems with variable initial conditions is investigated based on two-dimensional (2-D) system theory. The paper first introduces a 2-D tracking error system, and shows the effect of tracking errors against variable initial conditions. The sufficient conditions for the convergence of the learning cont...

متن کامل

Adaptive control of discrete-time nonlinear systems using recurrent neural networks - Control Theory and Applications, IEE Proceedings-

A learning and adaptive control scheme for a general class of unknown MIMO discretetime nonlinear systems using multilayered recurrent neural networks (MRNNs) is presented. A novel MRNN structure is proposed to approximate the unknown nonlinear input-output relationship, using a dynamic back propagation (DBP) learning algorithm. Based on the dynamic neural model, an extension of the concept of ...

متن کامل

Discrete-time repetitive optimal control: Robotic manipulators

This paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. The proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. This kind of control law is in the class of torque-based control in which the joint torques are generated by permanen...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001