The use of sliding modes to simplify the backstepping control method

Stotsky, Alexander; Hedrick, J. Karl; Yip, Pak

doi:10.1109/acc.1997.610875

Cited by 84 publications

(48 citation statements)

References 5 publications

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“…In recent years, the backstepping control method has been well developed, and various researches have achieved to combine the backstepping control method with other control methods. For example, in [9,10], based upon backstepping approach and sliding control method, a class of continuous output feedback controllers has been proposed. In [11], a wavelet adaptive backstepping controller is designed for a class of second-order nonlinear systems, in which the controller comprises a virtual backstepping controller and a robust controller.…”

Section: Introductionmentioning

confidence: 99%

“…It is worth pointing out that, in order to avoid the controller singularity problems, the virtual control coefficients in [9][10][11][12][13][14][15] are considered to be known and set equal to 1. However, the virtual control coefficients are always time-varying and even unknown in many cases (see, e.g., [16][17][18][19][20][21] and the references therein).…”

Section: Introductionmentioning

confidence: 99%

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Adaptive robust backstepping control for a class of uncertain dynamical systems using neural networks

Wang

2015

Nonlinear Dyn

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The problem of robust stabilization is considered for a class of nonlinear systems in the presence of structure uncertainties, external disturbances, and unknown time-varying virtual control coefficients. It is supposed that the upper bounds of the external disturbances and the virtual control coefficients are unknown. The unknown structural uncertainties are approximated by using neural networks (NNs). In particular, the prior knowledge about the weights and approximation errors of NNs is not required. The improved adaptation laws with σ -modification are employed to estimate the unknown parameters, which contain the upper bounds of the external disturbances and the virtual control coefficients, and the norm forms of weights and approximate errors of the NNs. Then, by making use of the updated values of these unknown parameters, a class of backstepping approach-based continuous adaptive robust state feedback controllers is synthesized. It is also shown that the proposed adaptive robust backstepping controller can guarantee the uniform asymptotic stability of such uncertain dynamical systems. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed controller.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive robust backstepping control for a class of uncertain dynamical systems using neural networks

Wang

2015

Nonlinear Dyn

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“…In the real application, most models of controlled system are uncertain or not accurate which makes the controller design to be a complex problem [1][2][3][4][5][6][7][8][9][10][11]. Some model are certain in some conditions, for example the parameters and the model of the controlled system will change unpredictably when conditions change.…”

Section: Introductionmentioning

confidence: 99%

Synchronous Control of Second Order Linear System Based on Sliding Mode Method

Li¹,

Ma²,

Wang³

et al. 2016

IJCA

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In order to solve the uncertain problem that parameters of system model are not accurate, a synchronous control method which is based on sliding mode method is proposed in this paper. A synchronous system which has the similar structures with the controlled system is constructed, then a control law is design to make the synchronous system trace the controlled system. So the controlled system can be controlled by controlling the synchronous system. Finally, numerical simulation was done the testify the rightness of the proposed method.

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“…In recent years, several control strategies, such as adaptive control [2][3][4], sliding mode control [5,6] and neural networks [7,8], have been integrated into the logical backstepping design procedure in order to enhance system robustness. An integral action has been widely used in adaptive backstepping control for eliminating steady state error, while a smooth sign function was adopted for avoiding chatter in sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

Extended Backstepping Sliding Controller Design for Chattering Attenuation and Its Application for Servo Motor Control

Chen

Peng

2017

Applied Sciences

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This paper presents a robust backstepping design for motion control in the presence of model uncertainties and exogenous disturbances. The main difficulty in dealing with motion control is to reduce the effect of friction, which exists in the moving mechanism and induces nonlinear behavior. In this study, the friction dynamic is considered as the external disturbance, and the proposed backstepping control algorithm is integrated with the sliding mode control, so that the effect of matching disturbances can be eliminated. The proposed approach guarantees the system asymptotic stability, globally, without significant chatter. Therefore, the developed algorithm can be realized for practical manufacturing motion control stages. Experiments including positioning and tracking controls are conducted to demonstrate the feasibility of the proposed method.

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The use of sliding modes to simplify the backstepping control method

Cited by 84 publications

References 5 publications

Adaptive robust backstepping control for a class of uncertain dynamical systems using neural networks

Adaptive robust backstepping control for a class of uncertain dynamical systems using neural networks

Synchronous Control of Second Order Linear System Based on Sliding Mode Method

Extended Backstepping Sliding Controller Design for Chattering Attenuation and Its Application for Servo Motor Control

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