An investigation of adaptive fuzzy sliding mode control for robotic manipulators

Lu, Xiaosong; Schwartz, Howard M.

doi:10.22215/etd/2007-07993

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…The next example introduced in [18] shows the capability of fuzzy systems from a function approximation point of view. It shows that fuzzy systems are good approx imators on a given nonlinear system.…”

Section: Fuzzy Systems and Examplesmentioning

confidence: 99%

Learning in pursuit-evasion differential games using reinforcement fuzzy learning

Faiya¹

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Section: Fuzzy Systems and Examplesmentioning

confidence: 99%

Learning in pursuit-evasion differential games using reinforcement fuzzy learning

Faiya¹

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Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology

Piltan¹,

Boroomand²,

Jahed³

et al. 2012

IJISA

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Design a nonlinear controller for second order nonlinear uncertain dynamical systems is the main challenge in this paper. This paper focuses on the design and analysis of a chattering free Mamdani's fuzzy-based tuning gradient descent optimal error-based fuzzy sliding mode controller for highly nonlinear dynamic six degrees of freedom robot manipulator, in presence of uncertainties. Conversely, pure sliding mode controller is used in many applications; it has two important drawbacks namely; chattering phenomenon and nonlinear equivalent dynamic formulation in uncertain dynamic parameter. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, Mamdani's performance/error-based fuzzy logic methodology with two inputs and one output and 49 rules is applied to pure sliding mode controller. Pure sliding mode controller and error-based fuzzy sliding mode controller have difficulty in handling unstructured model uncertainties. To solve this problem applied fuzzy-based tuning method to error-based fuzzy sliding mode controller for adjusting the sliding surface gain. Since the sliding surface gain is adjusted by gradient descent optimization method. Fuzzy-based tuning gradient descent optimal error-based fuzzy sliding mode controller is stable model-free controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in fuzzy-based tuning gradient descent optimal fuzzy sliding mode controller based on switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).

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An investigation of adaptive fuzzy sliding mode control for robotic manipulators

Cited by 2 publications

References 12 publications

Learning in pursuit-evasion differential games using reinforcement fuzzy learning

Learning in pursuit-evasion differential games using reinforcement fuzzy learning

Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology

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