Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah
This paper presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. The BPSO algorithm is an evolutionary computing techni...
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| Format: | Article |
| Language: | en |
| Online Access: | https://ir.uitm.edu.my/id/eprint/97562/1/97562.pdf https://ir.uitm.edu.my/id/eprint/97562/ |
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| Summary: | This paper presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. The BPSO algorithm is an evolutionary computing
technique put forward by (Kennedy and Eberhart, 1997). By representing its particles technique as probabilities of change (bit flip) of a binary string, the binary string was then used to select a set of repressors as the model structure, and the parameter estimated using QR decomposition. |
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