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Swarm cuckoo search for closed‐loop parameter identifications from different input signals
Author(s) -
Jin Qibing,
Wang Qi,
Qi Linfeng,
Jiang Beiyan,
He En
Publication year - 2016
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.22553
Subject(s) - cuckoo search , particle swarm optimization , swarm behaviour , metaheuristic , identification (biology) , computer science , multi swarm optimization , algorithm , closed loop , range (aeronautics) , mathematical optimization , search algorithm , random search , local search (optimization) , estimation theory , mathematics , engineering , aerospace engineering , control engineering , biology , botany
Abstract Most identification methods can only be applied to closed‐loop parameter identification by specific input signals. In order to solve the parameter estimation problem of a closed‐loop system with different test signals, a novel improved optimization method called the swarm cuckoo search is proposed. The swarm cuckoo search algorithm adopts a special approach of computing discovered probability, and it is different from other cuckoo search algorithms. The proposed algorithm has a strong ability to locate the global minimums with random initial values in the search range. Additionally, simulations also indicate that the proposed algorithm can increase the accuracy of the parameters when compared with particle swarm optimization algorithm.