Comparative Studies on Decentralized Multiloop PID Controller Design Using Evolutionary Algorithms
Saha, S; Das, S; Pakhira, A; et al.Mukherjee, S; Pan, I
Date: 14 May 2012
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publisher DOI
Abstract
Decentralized PID controllers have been designed in this paper for simultaneous tracking of individual process variables in multivariable systems under step reference input. The controller design framework takes into account the minimization of a weighted sum of Integral of Time multiplied Squared Error (ITSE) and Integral of Squared ...
Decentralized PID controllers have been designed in this paper for simultaneous tracking of individual process variables in multivariable systems under step reference input. The controller design framework takes into account the minimization of a weighted sum of Integral of Time multiplied Squared Error (ITSE) and Integral of Squared Controller Output (ISCO) so as to balance the overall tracking errors for the process variables and required variation in the corresponding manipulated variables. Decentralized PID gains are tuned using three popular Evolutionary Algorithms (EAs) viz. Genetic Algorithm (GA), Evolutionary Strategy (ES) and Cultural Algorithm (CA). Credible simulation comparisons have been reported for four benchmark 2x2 multivariable processes.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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