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Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm

Authors:

V. Rajinikanth,

K. LathaAuthors Info & Claims

Applied Computational Intelligence and Soft Computing, Volume 2012

Article No.: 22, Page 22

https://doi.org/10.1155/2012/214264

Published: 01 January 2012 Publication History

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Abstract

An enhanced bacteria foraging optimization (EBFO) algorithm-based Proportional + integral + derivative (PID) controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.

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Cited By

Jayachitra AVinodha R(2015)Genetic algorithm based PID controller tuning approach for continuous stirred tank reactorAdvances in Artificial Intelligence10.1155/2014/7912302014(9-9)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2014/791230
Rajinikanth VCouceiro MRangan PJayaraman B(2014)Multilevel Segmentation of Color Image using Lévy driven BFO AlgorithmProceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing10.1145/2660859.2660925(1-8)Online publication date: 10-Oct-2014
https://dl.acm.org/doi/10.1145/2660859.2660925
Latha KRajinikanth V(2012)2DOF PID controller tuning for unstable systems using bacterial foraging algorithmProceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing10.1007/978-3-642-35380-2_61(519-527)Online publication date: 20-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-35380-2_61

Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm
1. Computing methodologies
  1. Artificial intelligence
  2. Modeling and simulation
    1. Model development and analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems

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Published In

cover image Applied Computational Intelligence and Soft Computing

Applied Computational Intelligence and Soft Computing Volume 2012, Issue

January 2012

300 pages

ISSN:1687-9724

EISSN:1687-9732

Issue’s Table of Contents

Publisher

Hindawi Limited

London, United Kingdom

Publication History

Accepted: 16 August 2012

Revised: 23 July 2012

Received: 29 April 2012

Published: 01 January 2012

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Cited By

Jayachitra AVinodha R(2015)Genetic algorithm based PID controller tuning approach for continuous stirred tank reactorAdvances in Artificial Intelligence10.1155/2014/7912302014(9-9)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2014/791230
Rajinikanth VCouceiro MRangan PJayaraman B(2014)Multilevel Segmentation of Color Image using Lévy driven BFO AlgorithmProceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing10.1145/2660859.2660925(1-8)Online publication date: 10-Oct-2014
https://dl.acm.org/doi/10.1145/2660859.2660925
Latha KRajinikanth V(2012)2DOF PID controller tuning for unstable systems using bacterial foraging algorithmProceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing10.1007/978-3-642-35380-2_61(519-527)Online publication date: 20-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-35380-2_61

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