Paper Info
Title
A new discrete-time sliding-mode control with neural identification
Abstract
In this paper, we present a new sliding mode controller for a class of unknown nonlinear discrete-time sys- tems. We make the following two modifications: 1) The neural identifier which is used to estimate the unknown nonlinear system, applies new learning algorithms. The stability and non-zero properties are proved by dead-zone and projection technique. 2) We propose a new sliding surface and give a necessary condition to assure exponential decrease of the sliding surface. The time-varying gain in the sliding mode produces a low-chattering control signal. The closed-loop system with sliding mode controller and neural identifier is proved to be stable by Lyapunov method. I. INTRODUCTION Nowadays, almost all of control schemes are implemented on digital devices. Some advantages of the continuous time controllers are lost, because the control signal can only be applied at fixed time steps. In order to overcome these problems, we may design discrete-time controllers directly instead of discretization of continuous-time controllers. From the control point of view, modeling inaccuracies can be classified into two major kinds: parametric uncertainties and structure uncertainties. These uncertainties strongly effect on the model-based controllers. Therefore, practical design must address them explicitly. Robust control, adaptive control and sliding mode control can deal with model uncertainties very well. A typical structure of robust control is composed of a nominal part, which can be feedback linearization or inverse control, and an additional term aimed at canceling model uncertainties (12). Sliding-mode technique is very popular for this additional controller. Since the sliding-mode control switches the structure of the system during the evolution of the state vector to maintain the state trajectories in a predefined subspace, it is robust to parameter and struc- ture uncertainties and invariance to unknown disturbances. However, the control chattering caused by the discontinuity of the control action is undesirable in most applications. In continuous-time, the sliding mode condition is (22) v · v?0
Year
DOI
Venue
2006
10.1109/ACC.2006.1657584
american control conference
Keywords
DocType
Volume
Lyapunov methods,closed loop systems,discrete time systems,learning (artificial intelligence),neurocontrollers,nonlinear control systems,poles and zeros,stability,time-varying systems,variable structure systems,Lyapunov method,closed-loop system,dead-zone technique,discrete-time control,learning,neural identification,nonlinear discrete-time systems,nonzero properties,projection technique,sliding surface,sliding-mode control,stability,time-varying gain
Conference
1-12
ISSN
ISBN
Citations 
0743-1619
1-4244-0210-7
3
PageRank 
References 
Authors
0.43
10
3
Name
Order
Citations
PageRank
José De Jesús Rubio157436.29
Wen Yu228322.70
Andrés Ferreyra330.43