NDLI: Pareto robust reliability-based controller design for probabilistic uncertain systems using fuzzy rules

Content Provider	IEEE Xplore Digital Library
Author	Ahmadi, B. Ghamati, M. Jamali, A. Nariman-Zadeh, N.
Copyright Year	2011
Description	Author affiliation: Department of Mechanical, engineering, Faculty of Engineering, The University of Guilan, Rasht, Iran (Ahmadi, B.; Ghamati, M.) \|\| Department of Mechanical engineering, Faculty of Engineering, The University of Guilan, Rasht, Iran (Jamali, A.; Nariman-Zadeh, N.)
Abstract	In this paper, An optimal fuzzy system (OFS), instead of crisp threshold values, have been used for optimal reliability-based multi-objective Pareto design of robust state feedback controllers for a two-mass-spring system having parameters with probabilistic uncertainties. The objective functions that have been considered are, namely, the probabilities of failure of settling time (PTs), of control effort (Pu) and of stability of closed-loop system (Pi) in the reliability-based design optimization (RBDO) approach. A new multi-objective uniform-diversity genetic algorithm (MUGA) is used for Pareto optimum design of state feedback controllers for two-mass-spring problem. It is shown that multi-objective reliability-based Pareto optimization of the robust state feedback controllers using MUGA with OFS includes those that may be obtained by various crisp threshold values of probability of failures and, thus, remove the difficulty of selecting suitable crisp values. Besides, the multi-objective Pareto optimization of such robust feedback controllers using MUGA unveils some very important and informative trade-offs among those objective functions.
Starting Page	59
Ending Page	63
File Size	317129
Page Count	5
File Format	PDF
ISBN	9781612849195
e-ISBN	9781612849225
DOI	10.1109/INISTA.2011.5946156
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-15
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Probabilistic logic Control systems Reliability engineering Pareto Robust control Fuzzy rules Monte Carlo methods Robustness Multi-objective optimization Monte carlo simulation Uncertainties Fuzzy systems
Content Type	Text
Resource Type	Article

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