A fuzzy sliding controller for nonlinear systems

Wong, L.K.; Leung, F.H.F.; Tam, P.K.S.

doi:10.1109/41.904545

Cited by 106 publications

(41 citation statements)

References 9 publications

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“…FSMC is a hybrid development of sliding mode control and fuzzy logic control, where the switching controller term, K sign( S(X)), has been replaced by an inference fuzzy system [18].…”

Section: Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines

Ardjoun¹,

Abid²

2015

Turk J Elec Eng & Comp Sci

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Abstract:In this paper an indirect vector control using fuzzy sliding mode control is proposed for a double-fed induction generator (DFIG), applied for a wind energy conversion system in variable speed. The objective is to independently control the active and reactive power generated by the DFIG, which is decoupled by the orientation of the flux. The sliding mode control finds its strongest justification for the problem concerning the use of a robust nonlinear control law for the model uncertainties. As far as the fuzzy mode control is concerned, it aims at reducing the chattering effect. The obtained results show the increasing interest of such control in this system

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“…FSMC is a hybrid development of sliding mode control and fuzzy logic control, where the switching controller term, K sign( S(X)), has been replaced by an inference fuzzy system [18].…”

Section: Fuzzy Sliding Mode Controlmentioning

confidence: 99%

Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines

Ardjoun¹,

Abid²

2015

Turk J Elec Eng & Comp Sci

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“…The new stability analysis approach proposed in [25] is employed as the foundation in this study. In several essential aspects, it is different from the application of Lyapunov s theorem [20,26] , and it allows more applications. Specifically, it is suitable to control the processes where the derivative of the Lyapunov function candidate is not negative definite.…”

Section: System Stabilitymentioning

confidence: 99%

Position Control of Electro-hydraulic Actuator System Using Fuzzy Logic Controller Optimized by Particle Swarm Optimization

Wonohadidjojo

Kothapalli

Hassan

2013

Int. J. Autom. Comput.

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The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS.

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“…Generally speaking, this is a very difficult mission for researchers to develop such a control design for WMRs simultaneously possess (1) simple and easy implementation control structure, (2) error convergence, and (3) control performance guarantee design under the effects of internal and external disturbances. By the survey of existing literatures for the trajectory tracking design of WMRs, many investigations without taking the internal and external disturbances into account have been studied, and the developed tracking control methods for this trajectory tracking issue focus on four groups: (1) sliding mode control, [7][8][9][10][11][12] (2) feedback linearization, 13,14 (3) backstepping, [15][16][17] and (4) neural networks and fuzzy approaches. [18][19][20][21][22][23] Although these methods worked well without considering the effects of disturbances, there still exist several disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Wheeled mobile robot design with robustness properties

Chen

Huang

2018

Advances in Mechanical Engineering

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A trajectory tracking design for wheeled mobile robots is presented in this article. The design objective is to develop one nonlinear robust control law for the trajectory tracking problem of wheeled mobile robots in the presence of modeling uncertainties. The main contribution of this investigation is as follows. Under the effects of modeling uncertainties, an effective control design which can quickly converge tracking errors between the controlled wheeled mobile robot and the desired trajectory is derived mathematically. Generally, it is difficult to develop a nonlinear robust control design for the trajectory tracking problem of wheeled mobile robots due to the complexity and nonlinearity of the wheeled mobile robots' dynamics. Fortunately, based on a series analysis for the tracking error dynamics of the controlled wheeled mobile robot, one promising solution is obtained. For verifying the trajectory tracking performance of this proposed method, two scenarios are utilized in the simulations and the practical tests.

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A fuzzy sliding controller for nonlinear systems

Cited by 106 publications

References 9 publications

Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines

Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines

Position Control of Electro-hydraulic Actuator System Using Fuzzy Logic Controller Optimized by Particle Swarm Optimization

Wheeled mobile robot design with robustness properties

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