PID控制器参数模糊自整定研究
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摘要
本文主要研究的是PID控制器参数模糊自整定方法。首先对PID控制器与参数整定方法、模糊控制的基本原理、发展历史、研究现状和发展趋势进行了综述。然后，针对上述两种方法中存在的不足，将两种方法综合起来，取长补短，提出一种比较完善的模糊PID控制器参数自整定算法。
应用模糊集合理论和方法，把操作人员的PID参数整定经验总结成模糊规则模型，形成微机查询表格。微机根据控制系统的实际响应情况，运用模糊推理与决策实现对参数的在线调整。这种算法无需辨识系统的精确数学模型，只需在线检测出系统的期望输出和实际输出的偏差，通过判断其趋势从而决策出调整因子的大小，然后代入模糊自调整公式，即可整定出所有参数。其简单性和可实现性是显而易见的。
在Z-N法整定出PID参数的基础上，将本文提出的自调整公式应用于时滞二阶对象的控制。仿真结果表明，本文提出的算法优于传统的整定方法和相关文献的整定方法。
提出一种基于给定幅值裕度和相角裕度的PID参数模糊自调整算法，根据不同的幅值裕度和相角裕度，针对高阶对象进行了仿真。结果表明，该算法有较快的稳定速度。
In this dissertation, based on fuzzy inferences, a self-tuning PID is developed. The principle of PID control and Fuzzy control is described. Both their developing history and trend are discussed. A self-tuning PID controller based on fuzzy inferences is designed by joining the advantages of first one to a second one.
A model of fuzzy rules is built based on the operator's experiences, then it is changed into an inquiry form. According to system's real responding situation, fuzzy reasoning and decision are used to regulate PID controller's parameters online. Neither identification nor exactly mathematical model of controlled object is needed, it only needs to measure the controlled system's desired output and real output and compute the difference of them, then get the result of self-tuning factor by fuzzy inference and decision. After attaining the self-tuning factor, we can tune all PID controller parameters by the self-tuning formulas. It is obvious that this method is simple and feasible.
Designing a controller for a two-order plus time delay system , Simulation results show that the algorithm has better performance than other methods.
An algorithm of self-tuning PID parameters based on specified phase and gain margins is proposed. Simulation results of high order process show that the algorithm has high tracking speed.
应用模糊集合理论和方法，把操作人员的PID参数整定经验总结成模糊规则模型，形成微机查询表格。微机根据控制系统的实际响应情况，运用模糊推理与决策实现对参数的在线调整。这种算法无需辨识系统的精确数学模型，只需在线检测出系统的期望输出和实际输出的偏差，通过判断其趋势从而决策出调整因子的大小，然后代入模糊自调整公式，即可整定出所有参数。其简单性和可实现性是显而易见的。
在Z-N法整定出PID参数的基础上，将本文提出的自调整公式应用于时滞二阶对象的控制。仿真结果表明，本文提出的算法优于传统的整定方法和相关文献的整定方法。
提出一种基于给定幅值裕度和相角裕度的PID参数模糊自调整算法，根据不同的幅值裕度和相角裕度，针对高阶对象进行了仿真。结果表明，该算法有较快的稳定速度。
In this dissertation, based on fuzzy inferences, a self-tuning PID is developed. The principle of PID control and Fuzzy control is described. Both their developing history and trend are discussed. A self-tuning PID controller based on fuzzy inferences is designed by joining the advantages of first one to a second one.
A model of fuzzy rules is built based on the operator's experiences, then it is changed into an inquiry form. According to system's real responding situation, fuzzy reasoning and decision are used to regulate PID controller's parameters online. Neither identification nor exactly mathematical model of controlled object is needed, it only needs to measure the controlled system's desired output and real output and compute the difference of them, then get the result of self-tuning factor by fuzzy inference and decision. After attaining the self-tuning factor, we can tune all PID controller parameters by the self-tuning formulas. It is obvious that this method is simple and feasible.
Designing a controller for a two-order plus time delay system , Simulation results show that the algorithm has better performance than other methods.
An algorithm of self-tuning PID parameters based on specified phase and gain margins is proposed. Simulation results of high order process show that the algorithm has high tracking speed.
引文
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[3]Hang C C, Astrom K J, Ho W K, Refinement of the Ziegler-Nichols tuning formula, IEE.Proceeding, PartD, 1991, 138(2), 111～118
[4]汪洋，工业工程控制器的智能化参数整定研究，浙江大学博士学位论文，1998
[5]陶永华，尹怡欣，葛芦生，新型PID控制及其应用，北京，机械工业出版社1998．9
[6]Zadeh L A, Fuzzy sets, Information and Control, 1965, 8, 338～353
[7]焦李成，神经网络系统理论，西安，西安电子科技大学出版社，1990
[8]Ziegler J G, Nichols N B, Optimum setting for automatic controllers, Trans ASME[J], 1942, 64(8), 759～768
[9]Astrom K J, Hagglund T, Automatic tuning of simple regulators with specifications on phase and amplitude margins, Automatica, 1984, 20, 645～651
[10]Astrom K J, Hagglund T, Wallenbrog A, Automatic tuning of digital controllers with applications to HVAC plants, Automatica, 1993, 29(5), 1333～1343
[11]Hang C C, Astrom K J, Ho W K, Relay auto-tuning in the presence of static load disturbance, Automatica, 1993, 29(2), 563～564
[12]柴天佑，张贵军，基于给定的相角裕度和幅值裕度的PID参数自整定新方法，自动化学报，1997，23(2)，167～172
[13]李卓，萧德云，何世忠，基于Fuzzy推理的自调整PID控制器，控制理论与应用，1997，14(2)，238～242
[14]刘伯春，智能PID调节器的设计和实现，电气自动化，1995，3，18～21
[15]谭永红，基于BP神经网络的自适应控制，控制理论与应用，1994，11(1)，84～87
[16] . 赵有洁，国外公司研制的自整定PID控制器及其自整定方法，工业仪表 与自动化装置， 1995, 6, 6-9
[17] Cohen G H, Coon G A, Theoretical consideration of retarded control , Trans ASME, 1942, 75, 827-834
[18] Astrom K J, Toward intelligent control, IEEE Control Systems Magazine. 1989, 4, 60-64
[19] Kraus T W, Myron TJ, Self-tuning PID controller uses pattern recognition approach, Control Engineering, 1984, 6, 106-111
[20] Bristol E H, Pattern recognition: An alternative to parameter identification in adaptive control , Atomatica, 1977, 13, 197-202
[21] Astrom K J, Hagglund T, Automatic tuning of PID Controllers, Research Triangle Park, North Carolina: Instrument Society of America, 1988
[22] Bristol E H.A , simple adaptive system for industrial control, Instrumentation Technology, 1967, 6
[23] Callaghan P J, Lee P L, Newell RB, Evaluation of Foxboro controller, Process Control Engineering, 1986, 5, 38-40
[24] Hagglund T, Astrom K J, Industrial adaptive controllers based on frequency response techniques, Automatica, 1991, 27, 4, 599-609
[25] , 王伟，张晶涛，柴天佑，PID参数先进整定方法综述，自动化学报2000, 26(3) , 357-355
[26] Lundh M , Astrom K J, Automatic initialization of a robust self-tuning controller, Automatica, 1994, 30(11) , 1649-1662
[27] YusofR, Omatu S, KhaildM, Self-tuning PID contro: a multivariable derivation and application, Automatica, 1994, 30(12) , 1975-1981
[28] Schei T S, Automatic tuning of PID controllers based on transfer function estimation, Automatica, 1994, 30(12) , 1983-1989
[29] Voda A A , Landau L D, A method for the auto-calibration of PID controllers, Automatica, 1995, 31(1) , 41-53
[30] Lordon L, Tuning of PID controllers by the non-symmetrical optimum method, Automatica, 1997, 33(1) , 103-107
[31] Park J H, Sung S W, and Lee I B , Improved relay auto-tuning with static load disturbance, Automatic, 1997, 33(4) , 711-715
[32] Wang Q G, Zou B, Lee T H, and Bi Q, Auto-tuning of multivariable PID
controllers from decentralized relay feedback, Automatic, 1997, 33(3), 319～330
[32]Ho W K, Hang C C, and Cao L S, Tuning of PID controllers based on gain and phase margin specification, Automatica, 1995, 31, 497～502
[34]Ho W K, Lim K W, Xu W, Optimal gain and phase marign tuning for PID controllers, Automatica, 1998, 34(8), 1009～1014
[35]Astrom K J, Hagglund T, Hang C C, Ho W K. Automatic tuning and adaptation for PID controllers—A survey, Control Eng. Practice, 1993,1(4), 699～714
[36]Ho W K, Hang C C, Wojsznis W, Tao Q H, Frequency domain approach to self-tuning PID control, Control Eng. Practice, 1996, 4(6), 807～813
[37]Berger M, Self-tuning of a PI controller using fuzzy logic for a construction unit testing apparatus, Control Eng. Practice, 1996, 4(6), 785～790
[38]Rico J E, Bordons C, Camacho E F, Improving the robustness of deadtime compensating PI controllers, Control Eng. Practice, 1997, 5(6), 801～810
[39]Hang C C, Loh A P, Vasnani V U, Relay feedback auto-tuning of cascade controllers, IEEE Trans. On Control System Tech., 1994, 2(1), 42～45
[40]Mc Cormack A S, Godfrey K R, Rule-based auto-tuning based on frequency domain identification, IEEE Trans. On Control System Tech., 1998, 6(1), 43～61
[41]Astrom K J, Hagglund T, PID Controllers. 2nd Edition. Research Trianle Park, North Carolina, Instrument Society of America, 1995
[42]陈建勤，陈来九，一种新的PID调节器参数自整定方法，控制与决策，1993，8(1)，13～18
[43]汪洋，褚健，一种基于递推参数估计的PID参数自整定方法，信息与控制，1996，3，182～185
[44]刘镇，姜学智，李东海，PID控制参数整定方法，电子技术应用，1997，5，4～6
[45]曹永岩，毛维杰，孙优贤，冯旭著，现代控制理论的工程应用，杭州，浙江大学出版社，2000，5
[46]汪木兰，顾绳谷，模糊控制的回顾和发展趋势，工业仪表与自动化装置，1994，1，3～6
[47]彭声亮，模糊控制技术的应用与发展评述，自动化与仪器仪表，1995，2，7～11
[48]刘有才，刘增良，模糊专家系统原理与设计，北京，北京航空航天大学出版社，1995
[49]Ernest C, Control problems in fuzzy systems, Fuzzy Sets and Systems, 1982, 7, 257～273
[50]余永权，单片机与家用电器智能化技术，北京，电子工业出版社，1995
[51]吴晓帆，蔡自兴，自动化控制的发展与未来，石油化工自动化，1999，5(6)，6～8
[52]汪培庄，模糊集合论及其应用，上海，上海科学技术出版社，1983
[53]Joongseon Joh, Ye-Haw Chen, Reza Langari, On the stability isseus of linear, Takagi-Sugeno fuzzy models, IEEE Trans. Fuzzy Syst. 1998, 16, 3, 402～410
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