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Article type: Research Article
Authors: Rashidi, Farzan*
Affiliations: Department of Electrical and Computer Engineering, University of Hormozgan, Bandar-Abbas, Iran
Correspondence: [*] Corresponding author. Farzan Rashidi, Department of Electrical and Computer Engineering, University of Hormozgan, Bandar-Abbas, Iran. Tel./Fax: +98 76 33711041; E-mail: f.rashidi@ece.ut.ac.ir.
Abstract: Engine idle speed control problem has significant effects on fuel consumption, combustion stability and pollutions produced in urban traffics. In this paper, a Multi-Agent adaptive Critic based NeuroFuzzy Controller (MACNFC) for engine idle speed is presented to improve fuel efficiency, reduce emissions, and increase disturbance rejection capability while preventing the engine from stalling. The proposed MACNFC consists of a neurofuzzy controller, a learning mechanism and a set of fuzzy critic agents. It is assumed that each critic has been well designed to serve a particular objective. The role of the critics is to evaluate the controller performance in terms of satisfactory achievements of the control objectives through evaluation of plant output and provide appropriate continues reinforcement signals. If these signals become zero, it means that the critics are satisfied by the performance of the controller from their own point of view. If deviation of signals from zero become larger, it shows the more stress and more dissatisfaction. The reinforcement signals provided by critics contribute collaboratively to update neurofuzzy controller parameters via the learning mechanism for achieving predefined criteria and goals. The controller should modify its characteristics so that all reinforcement signals are decreased and consequently all critics are satisfied. To illustrate the effectiveness of the proposed method some simulations are given. Obtained results show that proposed method not only maintains the engine speed as close as possible to a desired value in the presence of various disturbances, but also improves fuel consumption for large production volumes of engine operating in different idle speed regimes.
Keywords: Idle speed control, engine model, fuel consumption, disturbance rejection, neurofuzzy controller, critic agent
DOI: 10.3233/JIFS-16083
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 817-829, 2017
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