Fault-tolerant fuzzy sliding-mode control for a class of MIMO underactuated nonlinear systems

Baklouti, Faten; Aloui, Sinda; Châari, Abdelkader

doi:10.1109/icosc.2017.7958691

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…Thirdly random Gaussian noises for the states and for the measurements both with zero mean values and with covariances q = 10 −2 and r = 10 −4 , respectively. D = 1 EKF is implemented as in (3) to (6). The Jacobean matrices F k , W k , H k , V k are defined in appendix A; EKF will provide the state estimate vector X = [ θ 1 , θ 1 , θ 2 , θ 2 ] T .The initial state and initial covariance conditions of the EKF are chosen to be X 0/0 = [0, 0, 0, 0] T and P 0/0 = ones (4,4), respectively.…”

Section: Simulation and Discussionmentioning

confidence: 99%

“…Soltanpour et al 2 , combined the feedback linearization control with the fuzzy sliding mode controller using Takagi-Sugeno fuzzy model, and the obtained result was free of undesirable chattering phenomenon. Morover, Baklouti et al 3 , combined the SMC, proportional integral (PI) controller and adaptive fuzzy systems for a robot manipulator; fuzzy system is used to approximate the unknown nonlinear functions and PI action is used to reduce the chattering phenomenon. However, Naoual et al 4 , designed a fuzzy sliding mode controller for a two-link manipulator, in which fuzzy logic is used to approximate only the unknown dynamic parts of the system.…”

Section: Introductionmentioning

confidence: 99%

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BBO optimization of an EKF for interval type-2 fuzzy sliding mode control

Medjghou¹,

Ghanai²,

Chafaa³

2018

IJCIS

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In this study, an optimized extended Kalman filter (EKF), and an interval type-2 fuzzy sliding mode control (IT2FSMC) in presence of uncertainties and disturbances are presented for robotic manipulators. The main contribution is the proposal of a novel application of Biogeography-Based Optimization (BBO) to optimize the EKF in order to achieve high performance estimation of states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the performances of EKF. The interval type-2 fuzzy logic system is used to avoid chattering phenomenon in the sliding mode control (SMC). Lyapunov theorem is used to prove the stability of control system. The suggested control approach is demonstrated using a computer simulation of two-link manipulator. Finally, simulations results show the robustness and effectiveness of the proposed scheme, and exhibit a more superior performance than its conventional counterpart.

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Section: Simulation and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BBO optimization of an EKF for interval type-2 fuzzy sliding mode control

Medjghou¹,

Ghanai²,

Chafaa³

2018

IJCIS

View full text Add to dashboard Cite

show abstract

“…In practice, this is difficult, and using them, the model obtained is usually uncertain. To overcome the problem of dynamic modelling and control, some researchers have proposed an adaptive control based on neural network control (Liu et al, 2014Liu and Zhang, 2013) and fuzzy logic approaches (Mai and Wang, 2014;Yoshimura, 2015;Faten Baklouti et al, 2016). For instance, non-model-based techniques have been developed for a different type of MMR with dynamic parameter uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Adaptive coordinated control of multi-mobile manipulator systems

Gauthier

Zhu

Brahmi

et al. 2017

IJDSSS

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This paper presents an adaptive coordinated control scheme for multiple mobile manipulator robots (MMR) moving a rigid object in coordination. The dynamic parameters of the object handled and of the mobile manipulators are considered unknown but constant. The control law and the adaptation of uncertain parameters are designed using the virtual decomposition (VDC) approach. This control approach was originally applied to multiple manipulator robot systems. The proposed control design ensures that the position error in the workspace converges to zero, and that the external force error is bounded. The global stability of the system using VDC is proven through the virtual stability of each subsystem. Numerical simulations and an experimental validation are carried out for two mobile manipulators transporting an object, and are compared with the results obtained using the computed torque approach in order to show the effectiveness of the proposed controller.

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Fault-tolerant fuzzy sliding-mode control for a class of MIMO underactuated nonlinear systems

Cited by 2 publications

References 11 publications

BBO optimization of an EKF for interval type-2 fuzzy sliding mode control

BBO optimization of an EKF for interval type-2 fuzzy sliding mode control

Adaptive coordinated control of multi-mobile manipulator systems

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