Robust Adaptive Dynamic Surface Control of Nonlinear Time-varying Systems in Strict-feedback Form

Elmi, Mojgan; Talebi, Heidar Ali; Menhaj, Mohammad Bagher

doi:10.1007/s12555-018-0663-z

Cited by 16 publications

(7 citation statements)

References 32 publications

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“…Substituting (40), (43) and (44) into (42) . (45) Now, define the final smooth quadratic Lyapunov function for entire non-linear control system as follows:…”

Section: Remark 1 the Derivative Of Intermediate Control Signal J −1mentioning

confidence: 99%

“…Then, the backstepping controller was further successfully extended to non-affine systems with dead zones [35], which expands its application field. There also exist other methods to deal with the 'explosion of differentiation' in the process of backstepping design, for example, the first-order filters replace the virtual control signals; therefore the dynamic surface control (DSC) scheme appeared [36][37][38][39][40][41][42][43]. Ling et al [44] normalized the adaptive parameters by using the maximum value of norm such that the running efficiency of the standard DSC algorithm is improved for flexible manipulators.…”

Section: Introductionmentioning

confidence: 99%

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Finite‐time adaptive neural dynamic surface control for non‐linear systems with unknown dead zone

Chen

Wang

2020

IET Control Theory & Appl

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This paper proposes a new adaptive neural network finite‐time dynamic surface control scheme for inaccurate non‐linear systems subjected to unknown dead zones. The ‘explosion of differentiation’ is eliminated by the first‐order filter in backstepping design. The parameter normalization scheme updates the coefficients of activation functions in the radial basis function neural networks. The dead zone inverse method estimates the dead zone parameters. It is proved that the proposed controller achieves the faster tracking performance and the boundedness of all signals in finite time. The contribution of this paper is that the presented controller not only has the advantages of transient performance and program execution time in comparison with traditional backstepping methods, but also its computational cost is lower than command filtered methods. Simulation experiment results are included to illustrate the effectiveness of the proposed scheme.

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“…Substituting (40), (43) and (44) into (42) . (45) Now, define the final smooth quadratic Lyapunov function for entire non-linear control system as follows:…”

Section: Remark 1 the Derivative Of Intermediate Control Signal J −1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Finite‐time adaptive neural dynamic surface control for non‐linear systems with unknown dead zone

Chen

Wang

2020

IET Control Theory & Appl

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“…In addition, Refs. [8][9][10][11], respectively, studied the robust adaptive control problems of strict-feedback nonlinear time delay systems with different system structures.…”

Section: Introductionmentioning

confidence: 99%

Exponential Stabilization for a Class of Strict-Feedback Nonlinear Time Delay Systems via State Feedback Control Scheme

Kong

Liu

2022

Processes

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This paper considers the exponential stabilization problem for a class of strict-feedback nonlinear systems with multiple time-varying delays, whose nonlinear terms satisfy the linear growth condition. The state feedback controller that relies on a positive parameter to be determined is constructed to deal with nonlinear terms. By tactfully introducing the Lyapunov–Krasovskii functional with an exponential function and selecting the applicable parameter to be determined, the implementable state feedback controller can be obtained to guarantee that the closed-loop system is exponentially stable. The proposed state feedback control scheme is finally applied to the control design of two-stage chemical reactor system, which illustrates the effectiveness of the control method.

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“…In this article, we will further focus on the robust adaptive dynamic surface control for a class of SISO uncertain nonlinear systems in strict‐feedback form under the unknown external disturbances. Compared with the works considering the adaptive dynamic surface control for a class of uncertain nonlinear systems in strict‐feedback form, there are a few works regarding to the robust adaptive dynamic surface control for uncertain nonlinear systems with additive external disturbances 35–43 . The types of adaptive law modifications have been presented such as σ‐modification,

\epsilon

‐modification and projection 44–47 …”

Section: Introductionmentioning

confidence: 99%

Robust adaptive dynamic surface control scheme for a class of single‐input and single‐output uncertain nonlinear systems in strict‐feedback form

Soukkou

Tadjine

Mokhtar

et al. 2022

Adaptive Control & Signal

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This article presents a robust adaptive dynamic surface control using σ-modification adaptation laws for a class of single-input and single-output (SISO) uncertain nonlinear systems in strict-feedback form with parametric uncertainties and external disturbances. The proposed scheme is developed by employing dynamic surface control based robust adaptive control technique.The key features of the approach are that, first, the problem of explosion of complexity inherent in the conventional adaptive backstepping control method is avoided, second, the proposed approach of σ-modification adaptation laws gives fast and accurate parameter estimation performance, and, third, the closed-loop signals of the system are proven to be uniformly ultimately bounded (UUB) by using the Lyapunov stability theory. We show the effectiveness of our approach by simulating an electromechanical system.

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Robust Adaptive Dynamic Surface Control of Nonlinear Time-varying Systems in Strict-feedback Form

Cited by 16 publications

References 32 publications

Finite‐time adaptive neural dynamic surface control for non‐linear systems with unknown dead zone

Finite‐time adaptive neural dynamic surface control for non‐linear systems with unknown dead zone

Exponential Stabilization for a Class of Strict-Feedback Nonlinear Time Delay Systems via State Feedback Control Scheme

Robust adaptive dynamic surface control scheme for a class of single‐input and single‐output uncertain nonlinear systems in strict‐feedback form

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