Application of memetic algorithm in modelling discrete-time multivariable dynamics systems

Ahmad, R. and Jamaluddin, H. and Hussain, Mohd Azlan (2008) Application of memetic algorithm in modelling discrete-time multivariable dynamics systems. Mechanical Systems and Signal Processing, 22 (7). pp. 1595-1609. ISSN 0888-3270, DOI

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Evolutionary algorithm (EA) such as genetic algorithm (GA) has demonstrated to be an effective method for identification of single-input-single-output (SISO) system. However, for multivariable systems, increasing the orders and the non-linear degrees of the model will result in excessively complex model and the identification procedure for the systems is more often difficult because couplings between inputs and outputs. There are more possible structures to choose from and more parameters are required to obtain a good fit. In this work, a new model structure selection in system identification problems based on a modified GA with an element of local search known as memetic algorithm (MA) is adopted. This paper describes the procedure and investigates the performance and the effectiveness of MA based on a few case studies. The results indicate that the proposed algorithm is able to select the model structure of a system successfully. A comparison of MA with other algorithms such as GAs demonstrates that MA is capable of producing adequate and parsimonious models effectively.

Item Type: Article
Additional Information: Cited By (since 1996): 5 Export Date: 5 March 2013 Source: Scopus CODEN: MSSPE Language of Original Document: English Correspondence Address: Ahmad, R.; Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai Johor, Malaysia; email: References: Johansson, R., (1993) System Modeling and Identification, , Prentice-Hall, Englewood Cliffs, NJ; Ljung, L., (1999) System Identification Theory for the User, , Prentice-Hall, Englewood Cliffs, NJ; Soderstrom, T., Stoica, P., (1989) System Identification, , Prentice-Hall, Hertfordshire; McElveen, J.K., Lee, K.R., Bennet, J.E., Identification of multivariable linear systems from input/output measurements (1992) IEEE Transactions on Industrial Electronics, 39 (3), pp. 189-193; P. Stoica, M. Jansson, A transfer function approach to MIMO system identification, in: Proceeding of the 36th Conference on Decision and Control, Arizona, 1992, pp. 2400-2405S. Munzir, H.M. Mohamed, M.Z. 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Uncontrolled Keywords: Dynamic system; Genetic algorithms; Memetic algorithm; Model structure selection; System identification; Algorithms; Bioelectric phenomena; Boolean functions; Broadband amplifiers; Computer networks; Dynamical systems; Gallium; Mathematical models; Multivariable systems; Scheduling algorithms; case studies; Complex modeling; Discrete time (DT); Elsevier (CO); Genetic algorithm (GA); identification procedures; Local search (LS); Memetic algorithm (MA); Multi variables; new model; Non-linear; Single-input single output (SISO) systems; System identification problems; Evolutionary algorithms.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jul 2013 03:51
Last Modified: 10 Feb 2021 03:47

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