An adaptive fuzzy sliding mode controller for robotic manipulators

Guo, Yuzheng; Woo, Peng-Yung

doi:10.1109/tsmca.2002.805804

Cited by 145 publications

(7 citation statements)

References 12 publications

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“…Adaptive fuzzy sliding mode control (Yuzheng and PengYung, 2003) is applied to calculate each element of the control gain (Sliding mode control for short in figures) with λ a =diag([5×10 3 ,10,10,3×10 3 , 3×10 3 ,10 3 ]) and A a =diag([5.5×10 3 ,11,11,3.3×10 3 , 3.3×10 3 ,1.1×10 3 ]).…”

Section: Numerical Simulationmentioning

confidence: 99%

“…Gaussian function is used as a based fuzzy membership function, where the fuzzy input makes up with posture tracking errors and control inputs, m = z 1 T , z 2 T , u T Â Ã T . Under the gravity, the desired tracking trajectory of the suspension platform along the x-direction is given as x p t ð Þ = g EA 1 4 m p l t ð Þ À (3) Adaptive fuzzy sliding mode control (Yuzheng and PengYung, 2003) is applied to calculate each element of the control gain (Sliding mode control for short in figures) with l a =diag([5 3 10 3 ,10,10,3 3 10 3 , 3 3 10 3 ,10 3 ]) and A a =diag ([5.5 3 10 3 ,11,11,3.3 spatiotemporal longitudinal responses of the suspension cable, floating sheave displacement, upper-lower boundary cable tensions, posture tracking results and control input, respectively. The spatiotemporal longitudinal responses of the 1-th suspension cable without platform disturbance given for simplification in different cases are shown in Figures 6-7.…”

Section: Dynamic Controlmentioning

confidence: 99%

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Adaptive fuzzy backstepping control of underactuated multi-cable parallel suspension system with tension constraint

Wang

Cao

2021

Transactions of the Institute of Measurement and Control

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Multi-cable parallel suspension system (MCPSS) is designed to lift a heavy object with rapid development of deep resources exploitation. An adaptive fuzzy backstepping control strategy combining with nonlinear disturbance observer is studied to synthetically control the posture for the underactuated MCPSS with tension constraint in this article. Firstly, a theoretical modelling of the MCPSS with boundary constraints is derived by the extended Hamilton’s Principle. Secondly, the parameter uncertainties and time-varying disturbances are compensated by the fuzzy system and nonlinear disturbance observer, respectively. Thirdly, an adaptive fuzzy backstepping feedback controller based on the reference model is proposed to suppress vibration and control posture of the suspension platform. Finally, an Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulation and a numerical calculation are used to illustrate the theoretical model and the proposed control performance.

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Section: Numerical Simulationmentioning

confidence: 99%

Section: Dynamic Controlmentioning

confidence: 99%

Adaptive fuzzy backstepping control of underactuated multi-cable parallel suspension system with tension constraint

Wang

Cao

2021

Transactions of the Institute of Measurement and Control

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“…Among various fuzzy structures, Takagi-Sugeno (T-S) fuzzy logic is widely using in control and identification purposes. Especially, it can be efficiently combined with soft-computing algorithms [3].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless the principal drawback of SMC induced from its on-off control issue, namely chattering effect. In order to remove such phenomenon, a saturated equation is often used [3] linked to the sliding surface. The disadvantage of this is that such linkage can spoil Lyapunov asymptotical stability of the investigated nonlinear system.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Fuzzy Sliding Mode Control for Uncertain PAM Robot Arm Plant Enhanced with Evolutionary Technique

Ánh¹,

Kien²

2021

IJCIS

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This paper introduces an enhanced fuzzy sliding mode control (EFSMC) algorithm used for controlling the uncertain pneumatic artificial muscle (PAM) robot arm containing external disturbances. The nonlinear features of investigated PAM robot arm system are approximated using fuzzy logic. Moreover, the coefficients of fuzzy model are optimum selected by evolutionary differential eveloution (DE) technique. The new EFSMC algorithm is designed based on the traditional sliding mode controller in which the adaptive fuzzy rule is developed based on the Lyapunov stability theory and is fuzzified with Mandani fuzzy scheme. As a consequent, the closed-loop stability of nonlinear uncertain PAM robot arm system is guaranteed to follow the global asymptotic stability. Experimental results are shown. It is evident that the proposed adaptive fuzzy rule suitable with the EFSMC controller which ensures an outperforming method in comparison with other advanced control approaches.

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“…If the uncertainties and external disturbances are sufficiently compensated, there is no need to use the discontinuous feedback control law to achieve the sliding mode and, therefore, the chattering phenomenon can be eliminated. For example, in [16] and [22], two similar adaptive fuzzy sliding mode controllers for serial robotic manipulators were proposed in which an adaptive single-input single-output (SISO) fuzzy logic system (FLS) or SISO radial basic function networks (RBFNs) were used to approximate the discontinuous part of the control signal. These controllers can eliminate the chattering phenomenon and they do not need knowledge of the upper boundary of the uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Chattering-Free Neuro-Sliding Mode Control of 2-DOF Planar Parallel Manipulators

Kang

Suh

2013

International Journal of Advanced Robotic Systems

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This paper proposes a novel chattering free neuro‐sliding mode controller for the trajectory tracking control of two degrees of freedom (DOF) parallel manipulators which have a complicated dynamic model, including modelling uncertainties, frictional uncertainties and external disturbances. A feedforward neural network (NN) is combined with an error estimator to completely compensate the large nonlinear uncertainties and external disturbances of the parallel manipulators. The online weight tuning algorithms of the NN and the structure of the error estimator are derived with the strict theoretical stability proof of the Lyapunov theorem. The upper bound of uncertainties and the upper bound of the approximation errors are not required to be known in advance in order to guarantee the stability of the closed‐loop system. The example simulation results show the effectiveness of the proposed control strategy for the tracking control of a 2‐DOF parallel manipulator. It results in its being chattering‐free, very small tracking errors and its robustness against uncertainties and external disturbances

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An adaptive fuzzy sliding mode controller for robotic manipulators

Cited by 145 publications

References 12 publications

Adaptive fuzzy backstepping control of underactuated multi-cable parallel suspension system with tension constraint

Adaptive fuzzy backstepping control of underactuated multi-cable parallel suspension system with tension constraint

Hybrid Fuzzy Sliding Mode Control for Uncertain PAM Robot Arm Plant Enhanced with Evolutionary Technique

Chattering-Free Neuro-Sliding Mode Control of 2-DOF Planar Parallel Manipulators

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