Robust Adaptive Fuzzy Sliding Mode Control Design for a class of MIMO underactuated system

Aloui, Sinda; Pagès, O.; Châari, Abdelkader; Koubaa, Yassine

doi:10.3182/20110828-6-it-1002.03435

Cited by 20 publications

(21 citation statements)

References 4 publications

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“…The closed loop system including state feedback controller (21) and uncertain nonlinear system with disturbance (3) can be expressed (10) in which, the parameters k 1 ; k 2 ; ...; k n−1 of the state feedback controller are chosen in (6). They only guarantee the closed loop system stable but, the tracking quality of closed loop is not considered.…”

Section: Optimal Tracking Controlmentioning

confidence: 99%

“…Four trends will appear, the first trend consists in introducing a direct adaptive fuzzy control combined with sliding mode control [5] and [6] based on Lyapunov theory. The second trend is carried out in controller design based on universal approximation [7], [8] and [9], the indirect adaptive fuzzy control (IAFC) combined with sliding mode control (SMC) has attracted much attention.…”

Section: Introductionmentioning

confidence: 99%

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New Adaptive Neural Network for Uncertain Nonlinear System with Disturbance

Pham

Lai²

2017

REV J. Electron. Commun.

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Abstract-The paper deals with the problem of tracking control for a class of nonlinear systems in presence of the disturbances. The developed formation for the tracking control is taken into account as an adaptive neural network. The set of controller's parameter, which is a satisfy Hurwitz polynomial, is then updated by adaptive laws via a model reference system. In addition, the unknown nonlinear functions are estimated by radial basis functions neural network. The adaptive updated law based on radial basis functions neural network and a feed-forward correction is proposed to estimate both estimation errors of nonlinear functions and external disturbances, which is called lumped disturbances. The feed-forward correction term is calculated by the algebraic equation regarding the parameters of controller and the radial basis function. Moreover, this estimator (using estimating the lumped disturbance) is also used both in class of SISO nonlinear and MIMO nonlinear system. Thanks to Lyapunov's theory, asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, two examples of coupled tank liquid system and an active magnetic bearing system, are presented to illustrate the our proposed methods.

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Section: Optimal Tracking Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New Adaptive Neural Network for Uncertain Nonlinear System with Disturbance

Pham

Lai²

2017

REV J. Electron. Commun.

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“…16, an adaptive fuzzy sliding mode was considered for 2 DOF nonlinear systems. Aloui et al addressed 17 systems of equation (1) using a robust adaptive fuzzy controller. Due to the complex structure of the proposed control law, three fuzzy models were employed to approximate unknown dynamics and parameters.…”

Section: Introductionmentioning

confidence: 99%

Observer based robust neuro-adaptive control of non-square MIMO nonlinear systems with unknown dynamics

Sarand¹,

Karimi²

2017

IJCIS

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This paper addresses a robust adaptive control problem of non-square nonlinear systems with unmeasurable states. The systems are assumed to be multi-input/multi-output subject to dynamical uncertainties and external disturbances. The approach is studied for two cases, i.e., underactuated and over-actuated nonlinear systems. The new observer does not need to satisfy the SPR conditions. Moreover, a constant full-rank matrix with an adaptive gain is used to approximate the unknown gain matrix. Therefore, the proposed controller's structure simplifies its implementation. The unknown nonlinearity is estimated neural networks. Stability of the closed-loop system is proved using Lyapunov analysis. The feasibility of the proposed approach is validated by simulation examples.

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“…In fact, a singularity problem is faced while computing the inverse of a nonsquare matrix. To avoid this issue, Aloui et al [14] proposed an adaptive fuzzy sliding mode control (AFSMC) based on regular inverse to synthesize the continuous part of the sliding mode law. An additional term is added to the control law to compensate the approximation of the singular matrix.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Sliding Mode Tracking Control of Uncertain Underactuated Nonlinear Systems: A Comparative Study

Baklouti¹,

Aloui²,

Châari³

2016

Journal of Control Science and Engineering

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The trajectory tracking of underactuated nonlinear system with two degrees of freedom is tackled by an adaptive fuzzy hierarchical sliding mode controller. The proposed control law solves the problem of coupling using a hierarchical structure of the sliding surfaces and chattering by adopting different reaching laws. The unknown system functions are approximated by fuzzy logic systems and free parameters can be updated online by adaptive laws based on Lyapunov theory. Two comparative studies are made in this paper. The first comparison is between three different expressions of reaching laws to compare their abilities to reduce the chattering phenomenon. The second comparison is made between the proposed adaptive fuzzy hierarchical sliding mode controller and two other control laws which keep the coupling in the underactuated system. The tracking performances of each control law are evaluated. Simulation examples including different amplitudes of external disturbances are made.

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Robust Adaptive Fuzzy Sliding Mode Control Design for a class of MIMO underactuated system

Cited by 20 publications

References 4 publications

New Adaptive Neural Network for Uncertain Nonlinear System with Disturbance

New Adaptive Neural Network for Uncertain Nonlinear System with Disturbance

Observer based robust neuro-adaptive control of non-square MIMO nonlinear systems with unknown dynamics

Adaptive Fuzzy Sliding Mode Tracking Control of Uncertain Underactuated Nonlinear Systems: A Comparative Study

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