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A new research of identification strategy based on particle swarm optimization and least square |
Tong ZHANG1,2( ), Yahui WANG2, Anli YE2, Jian WANG3, Jianchao ZENG4 |
| 1. RIOH Transport Consultants Ltd., Research Institute of Highway, Ministry of Transport, Beijing 100088, China; 2. School of Electric and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China; 3. Department of Technical Conditions, National Institute of Metrology P.R.China, Beijing 100013, China; 4. Taiyuan University of Science and Technology, Taiyuan 030024, China |
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Abstract Within the heat and moisture system that is complex in the air-conditioning rooms of large space building, the existence of delay makes the stability cushion reduced, which thereby makes the estimated parameters more complex. In this paper, particle swarm optimization (PSO) is integrated with least square (LS) to improve least squares (short for PSOLS). LS, optimized by PSO, identifies the heat and moisture system parameters of the existence of delay in the air-conditioning rooms by sampling input and output data. In view of this delay system, the identification is an effective solution to nonlinear system which LS can not identify directly. The simulation results show that PSOLS is quite effective, and its global optimization has great potential.
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| Keywords
least square (LS)
particle swarm optimization (PSO)
system identification
air-conditioning room
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Corresponding Author(s):
ZHANG Tong,Email:zhang_tong@hotmail.com
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Issue Date: 05 September 2009
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