| An Intelligent Adaptive Fuzzy PID Controller Based on Multimodel Control Approach |
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| 作者姓名： | 任立红 丁永生 邵世煌 |
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| 作者单位： | Ren Lihong，Ding Yongsheng，Shao ShihuangDepartment of Automation and Electronic Information: Engineering，China Textile University，Shanghai，200051 |
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| 摘 要： | A novel intelligent adaptive fuzzy PHD controller based on multimodel control approach is presented in this paper.It can improve the system performance of the dynamic time- varying system at various operating conditions.The fuzzy PHD controller is implemented by combining a fuzzy PI with a fuzzy PD controller in a parallel structure. The parameters of the fuzzy PHD controller are linked, via analytical derivation, to the gains of the linear PID controller. The sum of error square is used as performance criterion to locate the model that best reresents the process among the multiple models, The desired control output to drive the process along the desired path is generated only by modifying the output scale factots GU_I and GU_D of the fuzzy PID controller, Among the prescribed models, the control signal of the nearestmmodel to the system is applied. The system can be driven to its original trajectory because of the robustness of the fuzzy PID controller, Computer simulation results show that the adaptiv
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An Intelligent Adaptive Fuzzy PID Controller Based on Multimodel Control Approach |
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| Ren Lihong,Ding Yongsheng,Shao Shihuang.An Intelligent Adaptive Fuzzy PID Controller Based on Multimodel Control Approach[J].Journal of Donghua University,1998(3). |
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| Authors: | Ren Lihong Ding Yongsheng Shao Shihuang |
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| Institution: | Ren Lihong,Ding Yongsheng,Shao ShihuangDepartment of Automation and Electronic Information: Engineering,China Textile University,Shanghai,200051 |
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| Abstract: | A novel intelligent adaptive fuzzy PID controller based on multimodel control approach is presented in this paper. It can improve the system performance of the dynamic time - varying system at various operating conditions. The fuzzy PID controller is implemented by combining a fuzzy PI with a fuzzy PD controller in a parallel structure. The parameters of the fuzzy PCD controller are linked, via analytical derivation, to the gains of the linear PID controller. The sum of error square is used as performance criterion to locate the model that best represents the process among the multiple models. The desired control output to drive the process along the desired path is generated only by modifying the output scale factors GU1 and GU0 of the fuzzy PID controller. Among the prescribed models, the control signal of the nearest model to the system is applied. The system can be driven to its original trajectory because of the robustness of the fuzzy PID controller. Computer simulation results show that the adaptive fuzzy control system appears to be robust and stable even under a sudden and significant change in the system output in either direction. |
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| Keywords: | fuzzy PID multimodel adaptive control |
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