Multiobjective Multipath Adaptive Tabu Search for Optimal PID Controller Design | Zendy

Deacha Puangdownreong | Zendy

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Multiobjective Multipath Adaptive Tabu Search for Optimal PID Controller Design

Author(s) -

Deacha Puangdownreong

Publication year - 2015

Publication title -

international journal of intelligent systems and applications

Language(s) - English

Resource type - Journals

eISSN - 2074-9058

pISSN - 2074-904X

DOI - 10.5815/ijisa.2015.08.07

Subject(s) - tabu search , computer science , pid controller , metaheuristic , mathematical optimization , multipath propagation , guided local search , multi objective optimization , controller (irrigation) , control theory (sociology) , algorithm , control (management) , control engineering , mathematics , artificial intelligence , engineering , machine learning , channel (broadcasting) , temperature control , computer network , agronomy , biology

The multipath adaptive tabu search (MATS) has been proposed as one of the most powerful metaheuristic optimization search techniques for solving the combinatorial and continuous optimization problems. The MATS employing the adaptive tabu search (ATS) as the search core has been proved and applied to various real-world engineering problems in single objective optimization manner. However, many design problems in engineering are typically multiobjective under complex nonlinear constraints. In this paper, the multiobjective multipath adaptive tabu search (mMATS) is proposed. The mMATS is validated against a set of multiobjective test functions, and then applied to design an optimal PID controller of the automatic voltage regulator (AVR) system. As results, the mMATS can provide very satisfactory solutions for all test functions as well as the control application.

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