| Acceleration Factor Harmonious Particle Swarm Optimizer |
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| 作者姓名： | Jie Chen Feng Pan Tao Cai |
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| 作者单位： | Jie Chen，Feng Pan，Tao Cai Department of Automatic Control，School of Information Science and Technology，Beijing Institute of Technology，Beijing 100081，PRC |
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| 基金项目： | The work was supported by the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutes of MOE, PRC |
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| 摘 要： | A Particle Swarm Optimizer (PSO) exhibits good performance for optimization problems, although it cannot guarantee convergence to a global, or even local minimum. However, there are some adjustable parameters, and restrictive conditions, which can affect the performance of the algorithm. In this paper, the sufficient conditions for the asymptotic stability of an acceleration factor and inertia weight are deduced, the value of the inertia weight ω is enhanced to (-1,1). Furthermore a new adaptive PSO algorithm - Acceleration Factor Harmonious PSO (AFHPSO) is proposed, and is proved to be a global search algorithm. AFHPSO is used for the parameter design of a fuzzy controller for a linear motor driving servo system. The performance of the nonlinear model for the servo system demonstrates the effectiveness of the optimized fuzzy controller and AFHPSO.
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| 关 键 词： | 模糊控制 加速系数 微粒群最优化 渐近稳定度 全局收敛性 |
| 收稿时间： | 2005-03-01 |
| 修稿时间： | 2005-09-12 |
Acceleration factor harmonious particle swarm optimizer |
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| Jie Chen Feng Pan Tao Cai.Acceleration Factor Harmonious Particle Swarm Optimizer[J].International Journal of Automation and computing,2006,3(1):41-46. |
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| Authors: | Jie Chen Feng Pan Tao Cai |
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| Affiliation: | (1) Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing, 100081, PRC |
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| Abstract: | A Particle Swarm Optimizer (PSO) exhibits good performance for optimization problems, although it cannot guarantee convergence to a global, or even local minimum. However, there are some adjustable parameters, and restrictive conditions, which can affect the performance of the algorithm. In this paper, the sufficient conditions for the asymptotic stability of an acceleration factor and inertia weight are deduced, the value of the inertia weight ω is enhanced to (-1, 1).Furthermore a new adaptive PSO algorithm - Acceleration Factor Harmonious PSO (AFHPSO) is proposed, and is proved to be a global search algorithm. AFHPSO is used for the parameter design of a fuzzy controller for a linear motor driving servo system. The performance of the nonlinear model for the servo system demonstrates the effectiveness of the optimized fuzzy controller and AFHPSO. |
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| Keywords: | Particle swarm optimizer acceleration factor harmonious PSO asymptotic stability global convergence fuzzy control |
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