Fuzzy switching for multiple model adaptive control in manipulator robot

• Autorzy: Kharabian B. , Bolandi H. , Smailzadeh S. M. , Mousavi Mashhadi S. K.

Identyfikatory

DOI

10.14313/JAMRIS_1-2017/7

• Języki publikacji: EN

Abstrakty

EN

In this paper, fuzzy logic is used to perform switching controllers for Multiple Model Adaptive Control (MMAC) in manipulator robot. In the cases which uncertainty bounds of system’s parameters are large, the performance and stability issue of system are considerable concerns. Multiple Model Adaptive Control approach can be useful method to stabilize these kinds of systems. In this control method, the uncertainty bound is divided into several smaller bounds. As a result, the process of stabilization would be streamlined. In this regard, one estimation is obtained for uncertain parameter in every minor bound, and based on estimation errors designed controller can alter. In order to avoid switching controllers and pertinent challenges a summation of controllers with coefficient tuned by fuzzy logic is considered. Simulation results substantiate the efficacy of this method.

Słowa kluczowe

EN

manipulator robot; fuzzy logic; multiple model; adaptive control; switching

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2017
• Tom: Vol. 11, No. 1
• Strony: 53--56
• Opis fizyczny: Bibliogr. 19 poz., rys.

Twórcy

autor

Kharabian B.

• Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

autor

Bolandi H.

• Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

autor

Smailzadeh S. M.

• Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

autor

Mousavi Mashhadi S. K.

• Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).