Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form

By T. Zhang, Shuzhi Sam Ge. at - Automatisierungstechnik, 2008

756 citations recorded by the source corpus.

Subfields: Computational Mechanics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/2ea168095b2fdade1995bec8d84d8413aaf42ed1

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In Computational Mechanics

In Control and Systems Engineering

Citations in the corpus

Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems (2011, methodology): “To overcome is the problem of “explosion of complexity” inherent in the aforementioned adaptive fuzzy or neural network backstepping design methods, several adaptive fuzzy or neural backstepping control approaches have been developed based on the socalled Dynamic Surface Control (DSC) technique [17]”
A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems (2014, methodology): “…2003; Labiod & Guerra, 2007; Ren et al., 2009; Wang, Chien et al., 2011, 2010; Wang, Ge et al., 2010; Wang et al., 2006; Wang, Liu et al., 2011; Zhang & Ge, 2008; Zhang et al., 2010, 2012), the Taylor series expansion (Leu et al., 2005), and the contraction mapping method (Park, Huh et al.,…”
Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique (2011, methodology): “Remark 6: It is worth pointing out that the proposed algorithm for pure-feedback nonlinear time-delay systems is different from the existing works [20], [37], [43], [44].”
Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities (2010, background): “Assumption 2 [ 29 ]: For the continuous functions there exists known bounded functions and unknown constants such that satisfy”
Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems (2011, background): “For example, the authors in [27] and [28] proposed adaptive neural-backstepping DSC controllers for a class of SISO uncertain nonlinear systems without and with dead zone, respectively, while [29] dealt with adaptive neural-backstepping DSC of nonlinear systems with periodic disturbances.”
Finite-Time Adaptive Fuzzy Output Feedback Dynamic Surface Control for MIMO Nonstrict Feedback Systems (2019, methodology): “During the past decades, DSC technique had been applied to the adaptive fuzzy or neural control design process for uncertain nonlinear systems, for example, [30]–[38].”
Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation (2015, background): “References [18]–[20] proposed adaptive NN backstepping DSC state-feedback controllers for a class of SISO uncertain nonlinear systems without and with a dead zone.”
Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints (2013, background): “The main differences between our result and the ones in [29], [39], and [47] are as follows: 1) From the controlled systems, the results are obtained in [39] and [47] for deterministic systems and in [29] for the strict-feedback stochastic system without input saturation, and in this paper, we consi”
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints (2011, neutral): “Assumption 1 (Zhang & Ge, 2007, 2008 ).”
Adaptive Fuzzy Output Feedback Tracking Backstepping Control of Strict-Feedback Nonlinear Systems With Unknown Dead Zones (2012, methodology): “Remark 5: It should be mentioned that the state variables x1 and x2 in Example 1 are not available for measurement, the existing adaptive NN approaches that are developed by Zhang and Ge [37], [38] cannot be used to control the system (82).”
Adaptive Fuzzy Output Feedback Control of MIMO Nonlinear Systems With Unknown Dead-Zone Inputs (2013, background): “More recently, robust adaptive neural network backstepping controllers have been proposed in [38]–[40] for SISO and MIMO nonlinear strict-feedback systems with dead zone and without satisfying the matching condition.”
Direct Adaptive Neural Control for a Class of Uncertain Nonaffine Nonlinear Systems Based on Disturbance Observer (2013, background): “Assumption 3 [77]: For the system unknown external disturbance d(t) : R → R, there exists unknown positive constant dM such that ∀t ∈ R satisfy |d(t)| ≤ dM .”