Sliding mode control synthesis using fuzzy logic

Ghalia, Mounir Ben; Alouani, A.T.

doi:10.1109/acc.1995.521007

Cited by 30 publications

(18 citation statements)

References 11 publications

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“…Fuzzy logic provides an important tool for utilization of human expert knowledge in complement to mathematical knowledge. Many other researchers have attempted to apply the fuzzy approximator or fuzzy logic concepts to the conventional control techniques [7]- [10], and obtain many valid conclusion. Many of recent research have utilized an adaptive fuzzy sliding mode control approach (AFSMC) to handle uncertainties and disturbances, such as in [5] [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Immune Sliding Mode Control for a Class of Uncertain Nonlinear Systems

Yang

Huang

et al. 2007

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)

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In this paper, a stable adaptive fuzzy immune sliding mode controller(AFISMC) for a class of nonlinear uncertain systems is investigated. The fuzzy system is applied to approximate the unknown nonlinear function of plant, and then the estimation value of nonlinear function is used to design the control variable, the immune feedback system is used as a compensator for the fuzzy sliding control. The proposed approach does not need a bound to be known, only requiring that it exists, and has not any assumption for initial condition. The approach is applied to an inverted pendulum system via significant disturbances. Analysis of simulations reveals that proposed method is robust in the presence of uncertainties and bounded external disturbances.

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Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Immune Sliding Mode Control for a Class of Uncertain Nonlinear Systems

Yang

Huang

et al. 2007

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)

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“…Ghalia and Alouani (1995) uses a fuzzy boundary layer and compute the control action as a fuzzy combination of reaching and equivalent function terms. The resulting system has chattering elimination properties.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy boundary layer tuning for sliding mode systems as applied to the control of a direct drive robot

Erbatur

Çallı

2008

Soft Comput

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Chattering in the control signal is a significant problem in sliding mode control (SMC). The boundary layer approach is one of the many modifications proposed in the literature to avoid the chattering. In this approach, instead of the discontinuous SMC, a continuous feedback control law is employed in a boundary layer around the sliding surface. The thickness of the boundary layer is an important design parameter. This paper proposes a fuzzy online tuning method to adjust the boundary layer thickness for the best system performance without chattering. The method features the measurement of the chattering in the control signal. The paper validates the performance of the algorithm by experiments on a direct drive robot with a range of different payloads.

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“…Secondly, the system response can achieve fast response, stabilization, disturbance rejection, and insensitive to plant parameter variations. In the recent years, some researchers have proposed fuzzy control design methods based on the sliding mode control [29][30][31][32]. However, the control chattering is the main shortcoming of SMC, which can bring about unmodeled high-frequency dynamics of the system.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Adaptive Fuzzy Sliding Mode Control of Uncertain Multiple-Input Multiple-Output Nonlinear Systems

Chiang

2007

2007 IEEE International Fuzzy Systems Conference

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In this paper, the proposed observer-based robust adaptive fuzzy sliding mode control scheme can deal with the problem of robust stability for a class of uncertain multi-input multi-output (MIMO) nonlinear systems whose states are not available. The fuzzy basis function is used to approximate an unknown nonlinear function according to some adaptive laws, and then the state observer is designed for estimating the states of the plant, upon which a adaptive fuzzy sliding mode controller is investigated. Based on the Lyapunov stability theorem and the theory of variable structure control, the proposed robust adaptive fuzzy sliding mode control scheme can guarantee the robust stability of the whole closed-loop system and obtain good tracking performance. Finally, the simulation results are carried out on a two-link robot manipulator to illustrate the performance of the proposed approach.

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Sliding mode control synthesis using fuzzy logic

Cited by 30 publications

References 11 publications

Adaptive Fuzzy Immune Sliding Mode Control for a Class of Uncertain Nonlinear Systems

Adaptive Fuzzy Immune Sliding Mode Control for a Class of Uncertain Nonlinear Systems

Fuzzy boundary layer tuning for sliding mode systems as applied to the control of a direct drive robot

Observer-Based Adaptive Fuzzy Sliding Mode Control of Uncertain Multiple-Input Multiple-Output Nonlinear Systems

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