Forgetting Factor Nonlinear Functional Analysis for Iterative Learning System with Time-Varying Disturbances and Unknown Uncertain
نویسندگان
چکیده
This paper focuses on the iterative learning tracking control problem for a class of nonlinear system with time-varying disturbances. First, because of the mismatches in time-varying disturbances functions, a high-order feed-forward iterative learning control (ILC) is employed to change the original system into an iterative system. Secondly, a variable forgetting factor is developed to stabilize the system. Based on the feed-forward iterative learning controller, a memory controller is constructed for the nonlinear system. By choosing a new variable forgetting factor, we show that the designed continuous adaptive controller makes the solutions of the closed-loop system convergent to a ball exponentially. Finally, a numerical example is given to show the feasibility and effectiveness of the proposed method.
منابع مشابه
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 کاملAdaptive Approximation-Based Control for Uncertain Nonlinear Systems With Unknown Dead-Zone Using Minimal Learning Parameter Algorithm
This paper proposes an adaptive approximation-based controller for uncertain strict-feedback nonlinear systems with unknown dead-zone nonlinearity. Dead-zone constraint is represented as a combination of a linear system with a disturbance-like term. This work invokes neural networks (NNs) as a linear-in-parameter approximator to model uncertain nonlinear functions that appear in virtual and act...
متن کاملSecond Order Sliding Mode Observer-Based Control for Uncertain Nonlinear MEMS Optical Switch
This paper studies theuncertain nonlinear dynamics of a MEMS optical switch addressing electrical, mechanical and optical subsystems. Recently, MEMS optical switch has had significant merits in reliability, control voltage requirements and power consumption. However, an inherent weakness in designing control for such systems is unavailability of switch position information at all times due to t...
متن کاملA Discrete Robust Adaptive Iterative Learning Control for a Class of Nonlinear Systems with Unknown Control Direction
In this paper, a discrete robust adaptive iterative learning control is proposed for a class of uncertain nonlinear systems with unknown control direction and random bounded disturbances. Based on a new design methodology, the problem of unknown sign and upper bound of the time-varying input gain parameter can be solved. In order to deal with the uncertainties from random bounded disturbance an...
متن کاملPrediction-based Iterative Learning Control (PILC) for Uncertain Dynamic Nonlinear Systems Using System Identification Technique
Prediction-based Iterative Learning Control (PILC) is proposed in this paper for a class of time varying nonlinear uncertain systems. Convergence of PILC is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the ...
متن کامل