基于神经网络的燃煤锅炉液位内模控制系统研究
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摘要
论文针对火力发电厂锅炉汽包水位的控制进行研究。文章在总结内模控制的基础上，引入基于T-S模型的模糊神经网络，通过网络拓扑结构的优化和学习算法的改进来加快网络学习的速度。比如根据后件网络参数的特殊性，采用最小二乘的方法进行辨识，从而得到两种改进算法，并用模型对锅炉的汽包水位进行内模控制仿真研究。仿真结果证明了算法的有效性。
In this thesis, coal-fired boiler liquid control system in the thermal power plant , is studied. On summary internal model control foundation .based T-S modele of fuzzy neural networks , it speeds up through optimul network topology structure and studying algorithm forward improved .For example , empress piece network performance metric special ,using the least squared method di scriminate obtain two kinds of improvements. Simulate the modele of boiler liquid level internal model control .Simulation results show the algorithm is of better.
In this thesis, coal-fired boiler liquid control system in the thermal power plant , is studied. On summary internal model control foundation .based T-S modele of fuzzy neural networks , it speeds up through optimul network topology structure and studying algorithm forward improved .For example , empress piece network performance metric special ,using the least squared method di scriminate obtain two kinds of improvements. Simulate the modele of boiler liquid level internal model control .Simulation results show the algorithm is of better.
引文
[1] 舒迪前．预测控制系统及其应用．北京：机械工业出版社，1998
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[4] 刘保坤，王慧．曹明等．基于NN模型的直接优化预测器．[J]信息与控制，1998，(27)386～390
[5] 黄道平，朱学峰．基于一种集成模型的多变量非线性预测控制．控制理论与应用1999．16(1)．38-24
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[8] 金晓明等，基于模糊模型的非线性内模控制策略研究，控制与决策，12(3)，1997，228-232。
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[11] Daniel E. River, Low-order SISO controller tuning methods for the H_2, H~∞ and μobjective functuibs, Automatica, 1990,26(2),361-369.
[12] Eric coulibaly, Internal model predictive control, Automatica, 1995,31(10),1471-1482.
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[16] Shin-ichi norikawa, Zakeshi Furuhashi, and Yashiki Uchikawa, On Fuzzy Modeling using Fuzzy Neural Networks with the Back-Propagation Algorithm, 3(5),801-806.
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[18] J.S. Jang, "ANFIS:Adaptive-network-based fuzzy inference system" ,IEEE
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[19] Li Yan, Rad A.B, Wong Y.K. And Chan H.S.,.Model Based Control using Artificial Neural Networks, Proceedings of the IEEE international symposium on intelligent control, 1996,283-288.
[20] Matin T. Hagan and Mohammad B.Menhaj, Training Feedforward Networks with the the Marquardt Algorithm, IEEE Trans. On neural networks, 1994,5(6),989-993.
[21] 任庆昌，张永辉，具有非线性特性电加热炉的神经网络内模控制，第二届全球华人智能控制与智能自动化大会论文集，1997，782-785。
[22] 张乃尧、阎平凡，神经网络与模糊控制，清华大学出版社，1998。
[23] 王永骥、涂健，神经元网络控制，机械工业出版社，1998。
[24] 丛爽，面向MATLAB工具箱的神经网络理论与应用，中国科学技术大学出版社，1998。
[25] Wang,L.X.,"Adaptive Fuzzy System and Control:Design and Stability Analysis",Englewood cliffs,New Jersey,Inc.,1994。
[26] 任雪梅，龚至豪，基于模糊推理的非线性系统的神经网络辨识，第二届全球华人智能控制与智能自动化大会论文集，1997，1712-1716。
[27] 韩曾晋，自适应控制，清华大学出版社，1995。
[28] Yi Zhang, Jian Chu, JinChang Gao, A neuralfuzzy network structure for nonlinear system modeling, 14th World Congress of IFAC, 1999,97-102.
[29] Zhang and A.J.Morris, Fuzzy neural networks for nonlinear systems modelling, IEEE Proe.-Control Theory, 142(6),1995,551-156.
[30] Kasparian, V.,Batur, C.,Zhang, H.& Padovan, J., "Davidon least squares-based learning algorithm for feedforward neural networks," Neural networks, 1994,7(4):661-670.
[31] Holcomb, Y. & Morari, M., "Local training for radial basis function networks towards solving the hidden unit problem," Amercan Conference, 1993,2231-2235.
[32] Chen, S.,Cowan, C.F.N.& Grant, PM., " Orthogonal least spuares learning algorithm for radial basis function networks." IEEE Trans. on Neural.
[2] 杨熔．李永华．苏义鑫．用神经网络建立非线性系统模型研究．控制理论与应用1995，12(1)
[3] 黄殿辉．柴天佑．基于ANN模型的非线性自校正预测控制器[J]．自动化学报，1997，(3)396～39
[4] 刘保坤，王慧．曹明等．基于NN模型的直接优化预测器．[J]信息与控制，1998，(27)386～390
[5] 黄道平，朱学峰．基于一种集成模型的多变量非线性预测控制．控制理论与应用1999．16(1)．38-24
[6] 阎平凡，张长水．人工神经网络与模拟进化计算．清华大学出版社
[7] 张井冈等，模糊自适应内模控制，第二界全球华人智能控制与智能自动化大会论文集，1997，1811-1814。
[8] 金晓明等，基于模糊模型的非线性内模控制策略研究，控制与决策，12(3)，1997，228-232。
[9] 谭永红，自适应内模控制及其应用，自动化仪表，1991，12(4)，8-10。
[10] Aniruddha Datta, Adaptive internal model control design and stability analysis, Automatica, 1996,32(2),261-266.
[11] Daniel E. River, Low-order SISO controller tuning methods for the H_2, H~∞ and μobjective functuibs, Automatica, 1990,26(2),361-369.
[12] Eric coulibaly, Internal model predictive control, Automatica, 1995,31(10),1471-1482.
[13] 龚晓峰等，时滞系统PID控制器整定方法扩展，控制与决策，1998，13(4)，337-341。
[14] Tien Li Chia, Robust PID tuning using IMC technology, INTECH INDUSTRY, 1992,39(10),36-39.
[15] Marred Morari, Design of resilient processing plants, Chen. Engin. Science, 1986,41(6),1611-1630.
[16] Shin-ichi norikawa, Zakeshi Furuhashi, and Yashiki Uchikawa, On Fuzzy Modeling using Fuzzy Neural Networks with the Back-Propagation Algorithm, 3(5),801-806.
[17] GeorgeStephanopoulos, The2-PortControlSystem, Chem. Engin. science, 1986,41(6),1611-1630.
[18] J.S. Jang, "ANFIS:Adaptive-network-based fuzzy inference system" ,IEEE
Trans. Syst.,Man, Cybern.,1993,23,665-685.
[19] Li Yan, Rad A.B, Wong Y.K. And Chan H.S.,.Model Based Control using Artificial Neural Networks, Proceedings of the IEEE international symposium on intelligent control, 1996,283-288.
[20] Matin T. Hagan and Mohammad B.Menhaj, Training Feedforward Networks with the the Marquardt Algorithm, IEEE Trans. On neural networks, 1994,5(6),989-993.
[21] 任庆昌，张永辉，具有非线性特性电加热炉的神经网络内模控制，第二届全球华人智能控制与智能自动化大会论文集，1997，782-785。
[22] 张乃尧、阎平凡，神经网络与模糊控制，清华大学出版社，1998。
[23] 王永骥、涂健，神经元网络控制，机械工业出版社，1998。
[24] 丛爽，面向MATLAB工具箱的神经网络理论与应用，中国科学技术大学出版社，1998。
[25] Wang,L.X.,"Adaptive Fuzzy System and Control:Design and Stability Analysis",Englewood cliffs,New Jersey,Inc.,1994。
[26] 任雪梅，龚至豪，基于模糊推理的非线性系统的神经网络辨识，第二届全球华人智能控制与智能自动化大会论文集，1997，1712-1716。
[27] 韩曾晋，自适应控制，清华大学出版社，1995。
[28] Yi Zhang, Jian Chu, JinChang Gao, A neuralfuzzy network structure for nonlinear system modeling, 14th World Congress of IFAC, 1999,97-102.
[29] Zhang and A.J.Morris, Fuzzy neural networks for nonlinear systems modelling, IEEE Proe.-Control Theory, 142(6),1995,551-156.
[30] Kasparian, V.,Batur, C.,Zhang, H.& Padovan, J., "Davidon least squares-based learning algorithm for feedforward neural networks," Neural networks, 1994,7(4):661-670.
[31] Holcomb, Y. & Morari, M., "Local training for radial basis function networks towards solving the hidden unit problem," Amercan Conference, 1993,2231-2235.
[32] Chen, S.,Cowan, C.F.N.& Grant, PM., " Orthogonal least spuares learning algorithm for radial basis function networks." IEEE Trans. on Neural.