Output feedback NN tracking control for fractional-order nonlinear systems with time-delay and input quantization

Chen, Hua; Ning, Jinghua; Zhao, Guanglei; Li, Yafeng

doi:10.1016/j.neucom.2018.02.047

Cited by 46 publications

(34 citation statements)

References 24 publications

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“…Theorem 1. With Assumptions 1-3, virtual control laws (26), and feedback controller (25), the closed-loop system corresponding to (10) has the following properties:…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Almost Disturbance Decoupling for a Class of Fractional-Order Nonlinear Systems with Zero Dynamics

Zhao

Wang

et al. 2020

Complexity

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e problem of almost disturbance decoupling is addressed for fractional-order nonlinear systems. A new definition for the norm is proposed to describe the effect of disturbances on the output tracking error for fractional-order systems. Based on the Lyapunov stability theory and the backstepping design method, a tracking controller is constructed to make the output tracking error converge to zero without external disturbances and to attenuate the effect of disturbances on the tracking error at zero initial conditions. In order to validate these theoretical results, a numerical example and two practical examples are given.

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“…Theorem 1. With Assumptions 1-3, virtual control laws (26), and feedback controller (25), the closed-loop system corresponding to (10) has the following properties:…”

Section: Resultsmentioning

confidence: 99%

“…For instance, Wang et al addressed an adaptive fuzzy output tracking control law for a class of uncertain FOSs with backstepping technique [9]. An output feedback neural network tracking controller for fractional-order nonlinear systems is constructed with the backstepping method [10].…”

Section: Introductionmentioning

confidence: 99%

Almost Disturbance Decoupling for a Class of Fractional-Order Nonlinear Systems with Zero Dynamics

Zhao

Wang

et al. 2020

Complexity

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“…In [17], a robust adaptive neural network (NN) control scheme for a class of commensurate fractional order rotational mechanical system with disturbances and uncertainties is presented. In [18,19], a output feedback controller for the triangular commensurate fractional order nonlinear systems is given. For a class of commensurate fractional order systems with nonlinearities and backlash-like hysteresis, an adaptive fractional sliding VOLUME 4, 2016 mode controller based on dual radial basis function neural networks (RBF NNs) is presented in [20].…”

Section: Introductionmentioning

confidence: 99%

Design of Adaptive Fuzzy Controllers for a Class of Fractional Order Nonlinear MIMO Systems With Input Saturation

et al. 2020

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This paper develops a fractional order adaptive fuzzy backstepping control scheme for an incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems with external disturbance and input saturation. Combined with the adaptive and backstepping technique, the fuzzy logic system is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the incommensurate fractional order parameters update laws for fuzzy logic system, unknown parameters as well as the external disturbances are proposed in the controller to compensate the unknown nonlinearities, unknown parameters and disturbances. With the aids of the frequency distributed model of fractional integrator for the fractional order systems in the procedure of controller design, the stability of the closed loop system is established. At last, two simulation examples are demonstrated to verify the robustness and effectiveness of the proposed controller.

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“…Using the fractional order extension of the Lyapunov direct method, an adaptive backstepping control method for a class of commensurate fractional order nonlinear systems with unknown nonlinearity is developed in [34]. In [35] and [36], a output feedback control scheme for a class of triangular commensurate fractional order nonlinear systems is given. For a class of a commensurate fractional order rotational mechanical system with disturbances and uncertainties, a robust adaptive NN control is presented in [37].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of a Class of Incommensurate Fractional Order Nonlinear Systems With Input Dead-Zone

2019

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This paper develops a new adaptive control scheme for a class of incommensurate fractional order nonlinear systems with external disturbances and input dead-zone. Based on the backstepping algorithm, the radial basis function neural network (RBF NN) is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the fractional order parameters update laws for RBF NN are proposed as well as the fractional order nonlinear disturbance estimator to estimate the external disturbances. The adaptive RBF NN controller is designed based on the frequency distributed model of fractional integrator for the fractional order systems, and the stability of the closed loop system is proved. Finally, three simulation examples are given to verify the effectiveness and robustness of the proposed method. INDEX TERMS Fractional order systems, adaptive backstepping control, nonlinear system, neural networks (NNs), input dead-zone.

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Output feedback NN tracking control for fractional-order nonlinear systems with time-delay and input quantization

Cited by 46 publications

References 24 publications

Almost Disturbance Decoupling for a Class of Fractional-Order Nonlinear Systems with Zero Dynamics

Almost Disturbance Decoupling for a Class of Fractional-Order Nonlinear Systems with Zero Dynamics

Design of Adaptive Fuzzy Controllers for a Class of Fractional Order Nonlinear MIMO Systems With Input Saturation

Adaptive Control of a Class of Incommensurate Fractional Order Nonlinear Systems With Input Dead-Zone

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