全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于反演设计的块控型极值搜索系统一体化控制方法研究

DOI: 10.3724/SP.J.1004.2011.01114, PP. 1114-1129

Keywords: 极值搜索算法,一体化设计,反演控制,神经网络,反馈线性化

Full-Text   Cite this paper   Add to My Lib

Abstract:

?针对极值搜索控制系统(Extremumseekingcontrolsystems,ESCSs)设计中,极值搜索算法与控制器采取单独设计时易导致系统难以发挥其最佳性能,而现有的一体化设计方法却存在需要根据被控对象和具体的极值搜索算法进行不同形式的一体化建模的问题,以块控型的极值搜索控制系统为研究对象,提出了一套通用的极值搜索控制系统的一体化控制方法.首先针对块控型极值搜索控制系统,采用反馈线性化设计思想,构建出系统的伪虚拟控制量;然后以极值搜索算法得到的搜索变量作为其输入量,设计多层神经网络(Multilayerneuralnetworks,MNNs)逼近由近似模型与实际模型之间的差异而导致的误差项、状态变量的极值和极值的变化率,同时运用自适应参数和鲁棒项函数抵消神经网络逼近误差的影响;最后利用反演控制方法求取出系统的虚拟控制量和实际控制量.此一体化控制方法确保系统的状态跟踪误差、输出量与其极值之间的误差、极值搜索变量的跟踪误差以及神经网络各参数的估计误差均有界且指数收敛至系统原点的一个有限邻域内,且理论分析和仿真结果都验证了此方法的有效性.

References

[1]  Choi J Y, Krstic M, Ariyur K B, Lee J S. Extremum seeking control for discrete-time systems. IEEE Transactions on Automatic Control, 2002, 47(2): 318-323
[2]  Jonas P M, Mirko R B, Christian O P Gregor G, Rudikert K. Two-parameter extremum seeking for control of thermoacoustic instabilities and characterization of linear growth. In: Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit. Nevada, USA: AIAA, 2007. 1-17
[3]  Simeonov I, Noykoval N, Gyllenberg M. Identification and extremum seeking control of the anaerobic digestion of organic wastes. Cybernetics and Information Technologies, 2007, 7(2): 73-84
[4]  Dewasme L, Vande Wouwer A. Adaptive extremum-seeking control applied to productivity optimization in yeast fed-batch cultures. In: Proceedings of the 17th IFAC World Congress. Seoul, Korea: IFAC, 2008. 9713-9718
[5]  Zhong Z D, Huo H B, Zhu X J. Adaptive maximum power point tracking control of fuel cell power plants. Journal of Power Sources, 2008, 176(1): 259-269
[6]  Hu Yun-An, Zuo Bin, Li Jing. Integrated design of controller and extremum seeking algorithm with sliding mode. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2009, 37(3): 90-93 (胡云安, 左斌, 李静. 滑模极值搜索算法与控制器的一体化设计. 华中科技大学学报(自然科学版), 2009, 37(3): 90-93)
[7]  Krstic M. Performance improvement and limitations in extremum seeking control. Systems and Control Letters, 2000, 39(5): 313-326
[8]  Yu H, Ozguner U. Extremum-seeking control via sliding mode with periodic search signals. In: Proceedings of the 41st IEEE International Conference on Decision and Control. Las Vegas, USA: IEEE, 2002. 323-328
[9]  Pan Y D, Ozguner U, Acarman T. Stability and performance improvement of extremum seeking control with sliding mode. International Journal of Control, 2003, 76(9-10): 968-985
[10]  Zuo Bin, Hu Yun-An, Li Jing. Research on extremum seeking algorithm based on chaotic annealing recurrent neural network with parameter disturbances and its application. Acta Electronica Sinica, 2009, 37(12): 2651-2656 (左斌, 胡云安, 李静. 基于混沌退火的参数扰动递归神经网络极值搜索算法及其应用研究. 电子学报, 2009, 37(12): 2651-2656)
[11]  Shang F, Liu Y G. Adaptive output-feedback stabilization for a class of uncertain nonlinear systems. Acta Automatica Sinica, 2010, 36(1): 92-100
[12]  Tong S C, He X L, Zhang H G. A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control. IEEE Transactions on Fuzzy Systems, 2009, 17(5): 1059-1069
[13]  Zhu Sheng, Sun Ming-Xuan, He Xiong-Xiong. Iterative learning control of strict-feedback nonlinear time-varying systems. Acta Automatica Sinica, 2010, 36(3): 454-458 (朱胜, 孙明轩, 何熊熊. 严格反馈非线性时变系统的迭代学习控制. 自动化学报, 2010, 36(3): 454-458)
[14]  Liu Y J, Wang W, Tong S C, Liu Y S. Robust adaptive tracking control for nonlinear systems based on bounds of fuzzy approximation parameters. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2010, 40(1): 170-184
[15]  Ge S S, Zhang J. Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback. IEEE Transactions on Neural Network, 2003, 14(4): 900-918
[16]  Bianco C G L, Piazzi A, Aurelio P. A servo control system design using dynamic inversion. Control Engineering Practice, 2002, 10(8): 847-855
[17]  Cochran J, Krstic M. Nonholonomic source seeking with tuning of angular velocity. IEEE Transactions on Automatic Control, 2009, 54(4): 717-731
[18]  Zuo Bin, Hu Yun-An, Li Jing. A novel extremum seeking algorithm and its application to active control of combustion in aeroengines. Acta Aeronautica et Astronautica Sinica, 2009, 30(7): 1187-1196 (左斌, 胡云安, 李静. 一种新的极值搜索算法及在航空发动机燃烧主动控制中的应用. 航空学报, 2009, 30(7): 1187-1196)
[19]  Krstic M, Banaszuk A. Multivariable adaptive control of instabilities arising in jet engines. Control Engineering Practice, 2006, 14(7): 833-842
[20]  Bastin G, Nesic D, Tan Y, Mareels I. On automatic seeking of optimal steady-states in biochemical processes. In: Proceedings of the 7th IFAC Symposium on Nonlinear Control Systems. Pretoria, South Africa: IFAC, 2007. 814-819
[21]  Leyva R, Alonso C, Queinnec I, Gid-Pastor A, Lagrange D, Martinez-Salamero L. MPPT of photovoltaic systems using extremum-seeking control. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 249-258
[22]  Hu Yun-An, Zuo Bin, Li Jing. Research on integrated design for extremum seeking control systems. Control and Decision, 2008, 23(11): 1267-1271 (胡云安, 左斌, 李静. 极值搜索控制系统的一体化设计研究. 控制与决策, 2008, 23(11): 1267-1271)
[23]  Krstic M, Wang H H. Stability of extremum seeking feedback for general nonlinear dynamic systems. Automatica, 2000, 36(4): 595-601
[24]  Ariyur K B, Krstic M. Real-time Optimization by Extremum-seeking Control. New York: John Wiley & Sons, 2003. 5-20
[25]  Pan Y D, Ozguner U. Sliding mode extremum seeking control for linear quadratic dynamic game. In: Proceedings of the American Control Conference. Boston, USA: IEEE, 2004. 614-619
[26]  Hu Y A, Zuo B, Li J. An annealing recurrent neural network for extremum seeking control. International Journal of Information Technology, 2005, 11(6): 45-52
[27]  Wang C, Hill D J, Ge S S, Chen G R. An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica, 2006, 42(5): 723-731
[28]  Tong S C, Li Y M, Shi P. Fuzzy adaptive backstepping robust control for SISO nonlinear system with dynamic uncertainties. Information Sciences, 2009, 179(9): 1319-1332
[29]  Liu Bo, He Hai-Bo, Chen Sheng. Adaptive dual network design for a class of SIMO systems with nonlinear time-variant uncertainties. Acta Automatica Sinica, 2010, 36(4): 564-572
[30]  He Nai-Bao, Gao Qian, Jing Chang-Sheng, Gong Cheng-Long. Adaptive fuzzy control for MIMO non-affine nonlinear systems. Control Theory and Applications, 2010, 27(12): 1783-1786 (贺乃宝, 高倩, 姜长生, 龚成龙. MIMO非仿射非线性系统的自适应模糊控制. 控制理论与应用, 2010, 27(12): 1783-1786)
[31]  Park J H, Huh S H, Kim S H, Seo S J, Park G T. Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks. IEEE Transactions on Neural Network, 2005, 16(2): 414-422
[32]  Selmic R R, Lewis F L. Neural net backlash compensation with Hebbian tuning using dynamic inversion. Automatica, 2001, 37(8): 1269-1277
[33]  Zhang T, Ge S S, Hang C C. Design and performance analysis of a direct adaptive controller for nonlinear systems. Automatica, 1999, 35(11): 1809-1817

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133