Particle swarm optimization (PSO) approach to optimize GPC controller for pneumatic actuator system
Particle Swarm Optimization (PSO) is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. The algorithm is widely used and rapidly developed because of its easy implem...
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| 主要作者: | |
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2013
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| 在线阅读: | http://eprints.utm.my/id/eprint/43934/5/UbaidullahAzizMFKE2013.pdf http://eprints.utm.my/id/eprint/43934/ |
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| 总结: | Particle Swarm Optimization (PSO) is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. The algorithm is widely used and rapidly developed because of its easy implementation and few particles required to be tuned. In this project, one of the most popular Model Predictive Control namely Generalized Predictive Controller will be optimized and tuned by using PSO. The performance of GPC controller is optimized and evaluated by using PSO and Binary Particle Swarm Optimization (BPSO) is compared. These two (2) techniques are used as controller parameter setting to monitor the position of Pneumatic Actuator System. Result will be presented in simulation and real-time approach. MATLAB Simulink is used as the platform to obtain the result and a DAQ (Data Acquisition) card is used as the interface for real time experiment. |
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