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Software reconfigurable fuzzy PI-type controller for DC generator with separate excitation

Software reconfigurable fuzzy PI-type controller for DC generator with separate excitation

Pelc, Mariusz (2012) Software reconfigurable fuzzy PI-type controller for DC generator with separate excitation. In: 2012 17th International Conference on Methods & Models in Automation & Robotics (MMAR). IEEE Conference Publications . IEEE, Piscataway, N.J., USA, pp. 291-296. ISBN 978-1467321211 (doi:https://doi.org/10.1109/MMAR.2012.6347872)

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Abstract

In the typical computer control systems the core control algorithm itself is usually hard coded in a fixed form in a computer program. As such the control algorithm is not easily adjustable for run-time changing control goals and usually if any kind of reconfiguration of the algorithm is required, it can only be achieved via some kind of external tuning. In this paper a software architecture of Fuzzy Logic Controller algorithm for control of DC generator with separate excitation is presented. As such, the generator is a non-linear system due to the non-linear magnetization characteristic of its excitation circuit. Novelty of the paper lies in using the Open Decision Point component architecture to implement a flexible control algorithm where the core decision making logic is run-time loadable, configurable and replaceable which does not only enable parametric adjustment of control strategy but also changing the control strategy itself.

Item Type: Conference Proceedings
Title of Proceedings: 2012 17th International Conference on Methods & Models in Automation & Robotics (MMAR)
Additional Information: [1] This paper was presented at the 17th International Conference on Methods and Models in Automation and Robotics (MMAR 2012) held from 27-30 August 2012 in Miedzyzdrojie, Poland. [2] INSPEC Accession Number: 13117935
Uncontrolled Keywords: control systems, DC generators, fuzzy logic, fuzzy systems, pragmatics, software algorithms, tuning, DC motors, PI control, control engineering computing, electric generators, fuzzy control, machine control, nonlinear control systems, software architecture
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Faculty of Engineering & Science
Last Modified: 04 Mar 2022 13:08
URI: http://gala.gre.ac.uk/id/eprint/9696

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