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Adaptive functional-based neuro-fuzzy PID incremental controller structure

Fahmy, Ashraf and Abdel Ghany, A. M. 2015. Adaptive functional-based neuro-fuzzy PID incremental controller structure. Neural Computing and Applications 26 (6) , pp. 1423-1438. 10.1007/s00521-014-1807-6

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Abstract

This paper presents an adaptive functional-based neuro-fuzzy PID incremental controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input–output space of the three-term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral functions for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation. Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using bees algorithm and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA® type robot arm.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Business (Including Economics)
Engineering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: Springer
ISSN: 0941-0643
Last Modified: 09 Oct 2019 13:56
URI: http://orca-mwe.cf.ac.uk/id/eprint/69248

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