Robust tracking and model following for uncertain time‐delay systems with input nonlinearity

Abstract

This article proposes a novel adaptive sliding mode control (SMC) scheme to realize the problem of robust tracking and model following for a class of uncertain time‐delay systems with input nonlinearity. It is shown that the proposed robust tracking controller guarantees the stability of overall closed‐loop system and achieves zero‐tracking error in the presence of input nonlinearity, time‐delays, time‐varying parameter uncertainties and external disturbances. The selection of sliding surface and the existence of sliding mode are two important issues, which have been addressed. This scheme assures robustness against input nonlinearity, time‐delays, parameter uncertainties, and external disturbances. Moreover, the knowledge of the upper bound of uncertainties is not required and chattering phenomenon is eliminated. Both theoretical analysis and illustrative examples demonstrate the validity of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity 21: 66–73, 2015

An adaptive fast terminal sliding mode control combined with global sliding mode scheme for tracking control of uncertain nonlinear third-order systems

“…In [31], an adaptive fuzzy SMC is applied for a benchmark problem on a seismically excited highway bridge and is also integrated with clipped-optimal strategy to demonstrate its efficiency for semi-active dampers. In [32], an adaptive SMC scheme is proposed for the robust tracking and model following of uncertain time-delay systems with input nonlinearity. In [33], a robust adaptive SMC strategy is presented for a new introduced class of uncertain chaotic systems in the absence of any knowledge on the uncertainty bounds.…”

Adaptive Observer‐Based Global Sliding Mode Control for Uncertain Discrete‐Time Nonlinear Systems with Time‐Delays and Input Nonlinearity

“…When the controller is implemented in real physical systems, the limitations of actuators cause nonlinearity in the control input . In the literature, Assumption 1 has been applied in many studies …”

“…It is well known that SMC is an effective robust control scheme and has been extensively used to improve the stability, performance, and robustness of uncertain linear and nonlinear systems. Many studies on adaptive SMC have been presented in the literature . However, none of the above methods can deal with the robustness against parameter uncertainties, time‐delays, and input nonlinearity by using partial known state information in discrete‐time domain.…”

Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor

“…There are a number of models in the literature for [8], for example, the third expression of (A.2), for the bioprocess currently under study [31]. To demonstrate the controller performance, an additional term can be included in the calculation of as follows [18,51] …”