兆瓦级直驱永磁风力发电机组功率优化问题的研究
|
摘要
随着风电占电网的比重不断增加，电网对风电提出更高的需求，动态时风电系统为电网提供足够的能量支撑，稳态时要求其输出功率足够平稳。因此，对风电系统输出功率的控制显得越来越重要，功率优化控制已经成为大型风电机组的研究热点。在这样的背景下，本毕业论文以国家自然科学基金“考虑非线性不确定因素的风电机组动态载荷控制策略研究”(项目编号:51207095)课题为依托，以直驱永磁风电机组为对象，对风力发电系统的输出功率控制策略进行了深入的研究。目的是额定风速以下提高能量转换效率，额定风速以上稳定输出功率及抑制功率波动。主要研究工作归纳如下：
首先，本文研究了额定风速以下直驱永磁风电机组的功率优化问题的研究。在最佳叶尖速比风能转换理论基础上，深入分析了额定风速下直驱永磁风电机组功率优化存在的问题。在问题分析的基础上，设计了基于耗散系统理论框架的L2范数优化鲁棒速度控制器，该控制器采用动态误差方程构建系统模型，并将系统对干扰的抑制和对风速的跟踪要求归结为L2设计问题。为了求解控制律，应用Lyapunov函数构造存储函数，将系统对性能指标的要求转化为耗散稳定性问题，采用虚拟函数反推法求解控制器。为了克服风速波动对控制器的不良影响，采用扰动观测理论动态观测气动转矩变化，进行精确的前馈补偿，从而大大提高了系统的抗干扰能力，实现了风电机组的最大风能捕获，同时通过实验验证该控制策略的正确性。
第二，本文研究了额定风速以上直驱永磁风电机组功率优化问题的研究。首先，在风轮空气动力学和线性化控制理论基础上，深入分析了额定风速以上直驱永磁风电机组的恒功率控制问题。在问题分析的基础上，研究了非线性预测控制策略。将非线性预测控制用于变桨控制中，解决了风轮大惯量时滞问题及前馈补偿风速扰动问题，为了进一步提高预测模型对于参数易变的适应能力，采用泛模型进行预测模型参数优化设计，提高了预测模型的准确性及鲁棒性，大大降低了控制器参数设计的工作量。推导了基于泛模型的非线性预测控制策略的控制律。最后，通过仿真实验验证该控制策略的正确性。
第三，本文研究了额定风速以上直驱永磁风电机组的功率波动问题的研究。首先，在风轮空气动力学和变桨控制理论基础上，深入分析了额定风速以上直驱永磁风电机组的功率波动问题。在问题分析的基础上，应用泛模型理论和风轮空气动力学，研究了风轮载荷计算模型及功率波动变化趋势，推导出功率波动变化趋势模型，设计设计了一种特殊的独立变桨控制策略，该独立变桨控制解耦为统一变桨控制和摆振载荷偏差变桨控制，一方面，统一变桨控制采用第四章的基于泛模型的非线性预测控制，该控制策略维持风力机输出功率为额定值基本不变；另一方面，摆振载荷偏差变桨控制采用基于叶根摆振载荷变换桨距角反馈的泛模型控制策略。该控制策略通过实时检测每个叶片的叶根摆振载荷，以实测值与给定值的偏差此来反映叶片因风速变化引起的不平衡摆振载荷，利用泛模型理论建立的动态模型，将叶根摆振载荷偏差值变换为桨距角反馈调节量，对桨叶进行单独控制。控制的主要目标是实时跟踪响应风速的变化，通过桨距角反馈调节，减小由风切变、塔影效应对机组造成的不平衡载荷，从而抑制机组输出功率的波动。
最后，本文就直驱永磁风电机组的功率优化控制策略进行了实验研究。为了验证上述直驱永磁风电机组功率优化控制策略的正确性，构建了基于硬件在环方式的直驱永磁风电机组半实物仿真实验平台。对以上用于直驱永磁风电机组的功率优化控制方法进行了基于该平台的半实物仿真实验，实验结果进一步验证了本文提出的功率优化控制策略的可行性和有效性。
With the proportion of wind power in grid system increasing, it puts forward higherrequirements on wind power which is that the wind power can provide enough energy tosupport grid system in dynamic-state and the output power is smooth enough insteady-state. Therefore, output power control of wind power system seems more and moreimportant. The optimization control of power has become a hot spot of large wind turbineresearch. The direct-drive permanent magnet wind turbine is taken as the research object inthis dissertation based on the project supported by National Natural Science Foundation ofconsidering nonlinear dynamic load uncertainties of wind turbines control strategy research(project number:51207095) to further research the control strategy of wind turbine poweroutput. The goal of the research work is to improve energy conversion efficiency under therated wind speed, to stabilize output power and inhibit power fluctuation above the ratedwind speed. The main content of the dissertation is as following:
First of all, the direct-drive permanent magnet wind turbine power optimization underrated wind speed was studied. Based on the theory of optimal tip speed ratio wind energyconversion, the paper analyzed optimization problems of the direct-drive permanentmagnet wind turbine under the rated wind speed. Following the analysis, robust speedcontroller of the L2norm optimization was designed which applied the theory frameworkof dissipative system which adopted the dynamic error equation to build system model anddisturbance restraint and tracking requirements for wind speed are summed up L2designproblems. In order to solve the control law, the Lyapunov function is applied to constructthe storage function and requirements of performance index for system are changed intodissipative stability problem and the virtual function back stepping method is adopted tosolve the controller. In order to overcome the bad influence of wind speed fluctuation tothe controller, the paper used the perturbation theory and dynamic observations, andpneumatic torque changes is accurately feed forward compensated, which greatly improvesthe anti-interference ability of the system and realizes the maximum wind energy captureof wind turbines. Meanwhile，feasibility of the design method is verified by virtue ofcomputer simulation．
Secondly, the direct-drive permanent magnet wind turbine power optimization aboverated wind speed was researched. Based on the rotor aerodynamics and linear controltheory, this thesis deeply analyzed constant power control problem of direct-drivepermanent magnet wind turbine above the rated wind speed. Then, On the basis of problemanalysis, nonlinear predictive control strategy is applied to pitch control to solve the bigrotor moment of inertia time delay and the wind speed disturbance issues of feed-forward compensation. In order to further improve the prediction model for adaptive parametervariable, this thesis applied model free adaptive algorithm to optimize predictive modelparameter, which improve accuracy and robustness of predictive model, and greatly reducethe workload of the design of the controller parameters. Further, the thesis Derive controllaw of nonlinear predictive control strategy based on Generic model adaptive algorithm.Meanwhile, the simulation experiment verifies the correctness of the control strategy.
Thirdly, the direct-drive permanent magnet wind turbine power fluctuation aboverated wind speed was researched. Based on aerodynamics and pitch control theory, thethesis deeply analyzes power fluctuation problem of direct-drive permanent magnet windturbine above the rated wind speed. On the basis of the analysis, this thesis appliesmodelfree model theory and rotor aerodynamics to study wind load calculation model andthe power fluctuation change trend and deduce the power fluctuation trend model anddesign a special individual pitch control strategy. It decouple into unified pitch control anddeviation pitch control. On the one hand, unified pitch control adopts nonlinear predictivecontrol based on modelfree model of the fourth chapter, which maintain wind turbineoutput power rating unchanged; on the other hand, deviation pitch control adopts the bladeroot edgewise load changed into pitch Angle feedback control strategy based on modelfreemodel. The control strategy through the real-time detection of each blade root edgewiseload, the deviation of measured value with the given value to reflect rotor unbalancededgewise load caused by wind speed change and dynamic model is established by thetheory of modelfree and the blade root edgewise load deviation value transformation intothe pitch Angle feedback adjustment volume and single blade is individually controlled.Control's main goal is to real-time tracking response to the change of the wind speed,through pitch Angle feedback adjustment, reduce unbalanced edgewise load caused bywind shear and tower shadow effects, thus inhibiting output power fluctuation of windturbine.
At last, Experiment research of wind turbine power optimization was done. In order toverify the above power optimization control strategy, the dissertation construct simulationexperiment platform based on hardware in the loop, for the above control methods ofpower optimization, do the computer simulation and experiment based on the platform ofthe hardware-in-the-loop. On this basis, combining with typical the wind of wind farmssimulation, it further verify the application of the proposed control algorithm and strategyin the smoothing output power and improving power quality and the result is feasible andeffective.
首先，本文研究了额定风速以下直驱永磁风电机组的功率优化问题的研究。在最佳叶尖速比风能转换理论基础上，深入分析了额定风速下直驱永磁风电机组功率优化存在的问题。在问题分析的基础上，设计了基于耗散系统理论框架的L2范数优化鲁棒速度控制器，该控制器采用动态误差方程构建系统模型，并将系统对干扰的抑制和对风速的跟踪要求归结为L2设计问题。为了求解控制律，应用Lyapunov函数构造存储函数，将系统对性能指标的要求转化为耗散稳定性问题，采用虚拟函数反推法求解控制器。为了克服风速波动对控制器的不良影响，采用扰动观测理论动态观测气动转矩变化，进行精确的前馈补偿，从而大大提高了系统的抗干扰能力，实现了风电机组的最大风能捕获，同时通过实验验证该控制策略的正确性。
第二，本文研究了额定风速以上直驱永磁风电机组功率优化问题的研究。首先，在风轮空气动力学和线性化控制理论基础上，深入分析了额定风速以上直驱永磁风电机组的恒功率控制问题。在问题分析的基础上，研究了非线性预测控制策略。将非线性预测控制用于变桨控制中，解决了风轮大惯量时滞问题及前馈补偿风速扰动问题，为了进一步提高预测模型对于参数易变的适应能力，采用泛模型进行预测模型参数优化设计，提高了预测模型的准确性及鲁棒性，大大降低了控制器参数设计的工作量。推导了基于泛模型的非线性预测控制策略的控制律。最后，通过仿真实验验证该控制策略的正确性。
第三，本文研究了额定风速以上直驱永磁风电机组的功率波动问题的研究。首先，在风轮空气动力学和变桨控制理论基础上，深入分析了额定风速以上直驱永磁风电机组的功率波动问题。在问题分析的基础上，应用泛模型理论和风轮空气动力学，研究了风轮载荷计算模型及功率波动变化趋势，推导出功率波动变化趋势模型，设计设计了一种特殊的独立变桨控制策略，该独立变桨控制解耦为统一变桨控制和摆振载荷偏差变桨控制，一方面，统一变桨控制采用第四章的基于泛模型的非线性预测控制，该控制策略维持风力机输出功率为额定值基本不变；另一方面，摆振载荷偏差变桨控制采用基于叶根摆振载荷变换桨距角反馈的泛模型控制策略。该控制策略通过实时检测每个叶片的叶根摆振载荷，以实测值与给定值的偏差此来反映叶片因风速变化引起的不平衡摆振载荷，利用泛模型理论建立的动态模型，将叶根摆振载荷偏差值变换为桨距角反馈调节量，对桨叶进行单独控制。控制的主要目标是实时跟踪响应风速的变化，通过桨距角反馈调节，减小由风切变、塔影效应对机组造成的不平衡载荷，从而抑制机组输出功率的波动。
最后，本文就直驱永磁风电机组的功率优化控制策略进行了实验研究。为了验证上述直驱永磁风电机组功率优化控制策略的正确性，构建了基于硬件在环方式的直驱永磁风电机组半实物仿真实验平台。对以上用于直驱永磁风电机组的功率优化控制方法进行了基于该平台的半实物仿真实验，实验结果进一步验证了本文提出的功率优化控制策略的可行性和有效性。
With the proportion of wind power in grid system increasing, it puts forward higherrequirements on wind power which is that the wind power can provide enough energy tosupport grid system in dynamic-state and the output power is smooth enough insteady-state. Therefore, output power control of wind power system seems more and moreimportant. The optimization control of power has become a hot spot of large wind turbineresearch. The direct-drive permanent magnet wind turbine is taken as the research object inthis dissertation based on the project supported by National Natural Science Foundation ofconsidering nonlinear dynamic load uncertainties of wind turbines control strategy research(project number:51207095) to further research the control strategy of wind turbine poweroutput. The goal of the research work is to improve energy conversion efficiency under therated wind speed, to stabilize output power and inhibit power fluctuation above the ratedwind speed. The main content of the dissertation is as following:
First of all, the direct-drive permanent magnet wind turbine power optimization underrated wind speed was studied. Based on the theory of optimal tip speed ratio wind energyconversion, the paper analyzed optimization problems of the direct-drive permanentmagnet wind turbine under the rated wind speed. Following the analysis, robust speedcontroller of the L2norm optimization was designed which applied the theory frameworkof dissipative system which adopted the dynamic error equation to build system model anddisturbance restraint and tracking requirements for wind speed are summed up L2designproblems. In order to solve the control law, the Lyapunov function is applied to constructthe storage function and requirements of performance index for system are changed intodissipative stability problem and the virtual function back stepping method is adopted tosolve the controller. In order to overcome the bad influence of wind speed fluctuation tothe controller, the paper used the perturbation theory and dynamic observations, andpneumatic torque changes is accurately feed forward compensated, which greatly improvesthe anti-interference ability of the system and realizes the maximum wind energy captureof wind turbines. Meanwhile，feasibility of the design method is verified by virtue ofcomputer simulation．
Secondly, the direct-drive permanent magnet wind turbine power optimization aboverated wind speed was researched. Based on the rotor aerodynamics and linear controltheory, this thesis deeply analyzed constant power control problem of direct-drivepermanent magnet wind turbine above the rated wind speed. Then, On the basis of problemanalysis, nonlinear predictive control strategy is applied to pitch control to solve the bigrotor moment of inertia time delay and the wind speed disturbance issues of feed-forward compensation. In order to further improve the prediction model for adaptive parametervariable, this thesis applied model free adaptive algorithm to optimize predictive modelparameter, which improve accuracy and robustness of predictive model, and greatly reducethe workload of the design of the controller parameters. Further, the thesis Derive controllaw of nonlinear predictive control strategy based on Generic model adaptive algorithm.Meanwhile, the simulation experiment verifies the correctness of the control strategy.
Thirdly, the direct-drive permanent magnet wind turbine power fluctuation aboverated wind speed was researched. Based on aerodynamics and pitch control theory, thethesis deeply analyzes power fluctuation problem of direct-drive permanent magnet windturbine above the rated wind speed. On the basis of the analysis, this thesis appliesmodelfree model theory and rotor aerodynamics to study wind load calculation model andthe power fluctuation change trend and deduce the power fluctuation trend model anddesign a special individual pitch control strategy. It decouple into unified pitch control anddeviation pitch control. On the one hand, unified pitch control adopts nonlinear predictivecontrol based on modelfree model of the fourth chapter, which maintain wind turbineoutput power rating unchanged; on the other hand, deviation pitch control adopts the bladeroot edgewise load changed into pitch Angle feedback control strategy based on modelfreemodel. The control strategy through the real-time detection of each blade root edgewiseload, the deviation of measured value with the given value to reflect rotor unbalancededgewise load caused by wind speed change and dynamic model is established by thetheory of modelfree and the blade root edgewise load deviation value transformation intothe pitch Angle feedback adjustment volume and single blade is individually controlled.Control's main goal is to real-time tracking response to the change of the wind speed,through pitch Angle feedback adjustment, reduce unbalanced edgewise load caused bywind shear and tower shadow effects, thus inhibiting output power fluctuation of windturbine.
At last, Experiment research of wind turbine power optimization was done. In order toverify the above power optimization control strategy, the dissertation construct simulationexperiment platform based on hardware in the loop, for the above control methods ofpower optimization, do the computer simulation and experiment based on the platform ofthe hardware-in-the-loop. On this basis, combining with typical the wind of wind farmssimulation, it further verify the application of the proposed control algorithm and strategyin the smoothing output power and improving power quality and the result is feasible andeffective.
引文
[1]吴治坚.新能源和可再生能源的利用.北京：机械工业出版社，2006.
[2]2012年中国风电设备行业分析及市场研究报告.
[3]秦海岩.2009中国风电发展. http://wenku.baidu.com/view/9e4f5d563c1ec5da50e27040.html
[4]陈雷,邢作霞,潘建等.大型风力发电机组技术发展趋势.可再生能源,2003,(1):27-30.
[5]张新房.风力发电技术的发展及若干问题.现代电力，2003，20(5)：29-34.
[6]谢鲁冰，张振华，武国洪.直驱与双馈风机技术流派对比分析.应用能源技术，2012，176(8)：42-44.
[7]国家发展与改革委员会.能源发展“十一五”规划，2007.
[8]我国政策推动风电设备自主创新.中国投资咨询网，2008,5.
[9]范万新，苏志.国内外风能开发利用的现状和发展趋势.大众科技，2009，118(6)：131-133.
[10]张洋,李强,张晓东.风力发电机组控制技术综述.水利电力机械,2007,(7)：53-55.
[11]邓英，梁晶晶，王湘明等.减缓风力发电机组驱动链载荷的控制器.太阳能学报，2009，30(10)：1420-1423．
[12]刘颖明.永磁直驱风电机组控制技术研究：（博士学位论文）.沈阳：沈阳工业大学，2010.
[13]高指林.风力发电机组变桨距控制系统及其执行机构的研究：(硕士学位论文).武汉：武汉理工大学,2007.
[14]刑作霞.大型变速变距风力发电机组的柔性协调控制技术研究：(博士学位论文).北京：北京交通大学,2008.
[15]刘忠明，段守敏，王长路.风力发电齿轮箱设计制造技术的发展与展望.机械传动，2006，30（6）：1-6.
[16] E.Muljadi, C.P. Butterfield. Pitch-controlled variable-speed wind turbine generation. IEEETransactions on Industrial Applications,2001,37(1):240-246.
[17] N.Horiuchi, T. Kawahito. Torque and power limitations of variable speed wind turbines using pitchcontrol and generator power control. IEEE Power Engineering Society Summer Meeting，2001，1:638-643.
[18] W. L. Chen, Y. Y. Hsu. Unified voltage and pitch angle controller for wind-driven inductiongenerator system. IEEE Transactions on Aerospace and Electronic Systems.2008,44(3):913-926.
[19]高文元,祝振敏,井明波等.风电机组变桨距系统神经网络模糊自适应控制.武汉理工大学学报,2008,30(4)：533-536.
[20]王哲.大型风电机组变桨距控制策略研究：（博士学位论文）.沈阳：沈阳工业大学，2010.
[21]风电设备制造产业及公司分析.http://finance.sina.com.cn/stock/hyyj/20070202/14083307932.shtml.
[22]姚兴佳，宋俊等.风力发电机组原理与应用.北京：机械工业出版社，2009.
[23]叶杭冶.风电机组的控制技术.北京：机械工业出版社，2002.
[24]姚兴佳，刘国喜，朱家玲等.可再生能源及其发电技术.北京：科学出版社，2010.
[25]熊礼俭.风力发电新技术与发电工程设计、运行、维护及标准规范实用手册.北京：中国科学文化出版社，2005.
[26]Burton Tony, Sharpe David, Jenkins Niek. Wind energy handbook. New York: John Wiley&Sons,Ltd,2001.
[27]孟克其劳，陈虎，钱春震等.永磁直驱风力发电系统最大功率追踪策略研究.电力系统保护与控制，2012，40(22)：83-87.
[28]柳明，柳文.基于风速和空气密度估计的最大风能捕获.电网技术，2009，33(1)：56-60.
[29]王新生，吴吟箫，何川.基于风速预测的最大风能追踪控制系统仿真.电机与控制学报，2010，14(2)：20-24.
[30]刘姝，姚兴佳，王晓东等.模糊专家控制系统的最大风能追踪.微特电机，2012，40(9)：20-24.
[31]刘吉宏，吕跃刚，郭鹏等.风电系统最大风能追踪的智能模型预测控制.计算机工程与应用，2011，47(9)：228-232.
[32]赵亮，吕剑虹，向文国.采用极值搜索法的风电机组最大风能追踪控制.电网技术，2011，35(5)：171-175.
[33]付光杰，崔海龙，冉璇等.永磁同步风力发电机侧变流器控制策略.吉林大学学报，2011，29(5)：228-232.
[34]李游，成怡.直驱型永磁风力发电机的最大风能捕获影响因素分析.天津大学学报，2012，40(5)：70-74.
[35]汤天浩，陈新红，彭东恺等.直驱式永磁同步风力发电机稳态模型与最大功率跟踪控制.电源学报，2011，35(5)：11-15.
[36]殷明慧，张小莲，叶星等.一种基于收缩跟踪区间的改进最大功率点跟踪控制.中国电机工程学报，2012，32(27)：24-28.
[37]李晶，葛敏.最大风能追踪模糊控制器的仿真设计.风机技术，2010，35(6)：11-15.
[38]张文娟，高勇，杨媛.基于风力机参数辨识的最大风能捕获.电网技术，2009，33(17)：152-156.
[39]赵林坤.变速恒频风力发电系统转速鲁棒控制方法研究.长沙：长沙理工大学，2009.
[40]吴东吉.变速恒频双馈发电系统解耦控制研究.兰州：兰州理工大学.2008.
[41]李琳.双馈风力发电机滑模控制策略的研究.哈尔滨工业大学，2009.9.
[42]孔屹刚，王志新．大型风电机组模糊滑模鲁棒控制器设计与仿真[J]．中国电机工程学报，2008，28(14):136-141.
[43] Ruben P, Daniel S. Integer variable structure controllers for small wind energy systems. Proc of theIEEE Canadian Conf on Elec and Computer Engineering.1999:1067-1072.
[44] Battista H D, Mantz R J. Sliding mode control of torque ripple in wind energy conversion systemswith slip power recovery. Proc of the24th Annual Conf of IEEE，1998:651-656.
[45] Battista, R.J. Mantz, C.F. Christiansen. Dynamical sliding mode power control of wind driveninduction generators. IEEE Transactions on Energy Conversion,2000,15(4):451-457.
[46]Connor B. LQG Control of a constant speed horizontal axis wind turbine. The3rd IEEE Conf.onControl Appl,1994:251-252.
[47]郑雪梅，李琳，徐殿国.双馈风力发电系统低电压过渡的高阶滑模控制仿真研究.中国电机工程学报，2009，27：178-183.
[48] Song Y D, et al, Variable speed control of wind turbines using nonlinear and adaptivealgorithms. Journal of Wind Engineering and Industrial Aerodynamics,2000,85:293-308.
[49] D. Song, B.Dhinakaran.Control of wind turbines using nonlinear algorithms. American ControlConferences,2000:1551-1555.
[50]Qi Wang, Xiaohu Chen, Yanchao Ji. Fuzzy-based active and reactive control for brushlessdoubly-fed wind power generator system, APCCAS2006, Singapore,848-851.
[51]Xingjia Yao, Yanjun Jing, Zuoxia Xing. Direct torque control of a doubly-fed wind generator basedon grey-fuzzy logic. Proceedings of the2007IEEE, International Conference on Mechatronics andAutomation, August5-8,2007, Harbin, China,3587-3592.
[52]高文元，祝振敏.基于模糊自适应控制的风电机组变桨距系统.工业科技，2008，37(4)：45-46.
[53]钟声.模糊控制在变桨距恒速恒频风力发电机中的应用.应用技术，2008，36(2)：41-43.
[54]张先勇，吴婕，杨金明等.额定风速以上风力发电机组的恒功率H∞鲁棒控制.控制理论与应用，2008，25(2)：321-328.
[55] Liebst B S.A Pitch control system for the kamewa wind turbine.Dynamic Systems, Measurementand Control,1985:47-52.
[56]杨俊华，吴捷，杨金明等.风力发电系统中的最优控制策略综述.微特电机，2004，22(3)：30-42.
[57]张雅楠.变桨距与智能控制在风电机组中的应用.沈阳：沈阳工业大学，2010.
[58]邓英，梁晶晶，王湘明等.减缓风力发电机组驱动链载荷的控制器.太阳能学报，2009，30(10)：1420-1423.
[59]于振燕，张玮，张立强.基于遗传算法PID的风力机变桨距系统电液伺服控制.西华大学学报，自然科学版，2007，26(4)：64-65.
[60]陈思哲，吴捷，姚国兴等.基于微分几何的风力发电机组恒功率控制.控制理论与应用，2008(25)，2：336-340.
[61]赵林坤.变速恒频风力发电系统转速鲁棒控制方法研究.长沙：长沙理工大学，2009.
[62]周培毅，张新燕，张华中.基于遗传算法与BP神经网的风力发电机齿轮箱故障诊断研究.华北电力技术，2010，(7)：6-11.
[63]赵卓鹏，贾石峰.基于Elman神经网络的风力发电机组齿轮箱故障诊断研究.伺服控制，2010，6：65-66.
[64]许凌峰，徐大平，等.基于神经网络的风力发电机组变桨距复合控制.华北电力大学学报，2009，36(1)：28-34.
[65] Ekelund T. Yaw control for reduction of structural dynamic loads in wind turbines. Wind Eng. Ind.Aerodyn.,2000,:241-262.
[66]张玉华，李振凯.基于模糊控制的风力发电系统变桨距控制器的设计.现代电力，2007(24)6：58-61.
[67]郭鹏.风电机组非线性前馈与模糊PID结合变桨距控制研究.动力工程学报，2010(30)11：838-843.
[68]邢作霞，郑琼林.基于BP神经网络的PID变桨距风电机组控制.沈阳工业大学学报，2006，28(6)：681-686.
[69]师彪，李郁侠，于新花等.基于弹性自适应人工鱼群-BP神经网络的风轮节距控制环.农业工程学报，2010，26(1)：145-149.
[70] Shuhui Li, Wunsch D.C, OHair E.A. Using neural networks to estimate wind turbine powergeneration. IEEE Transactionsion on Energy Conversion,2001.
[71] Shi KL, Li H. A novel control of a small wind turbine driven generator based on neural networks.Piscataway NJ. Power Engineering Society General Meeting,2004,2:166-169.
[72] Murdoch A. Control design and performance analysis of a6mw wind turbine-generator. IEEETrans. PAS,1983:1340-1347.
[73] Ekelund T. Dynamics and control of structural loads of wind turbines. Proc of the AmericanControl Conf., Pennsylvania,1998.6:1720-1724.
[74] E.A.Bossanyi. Adaptive pitch control for a250kw wind turbine. Proc British Wind EnergyConference.1986:85-92.
[75] YD. Song, B.Dhinakaran.Control of wind turbines using nonlinear algorithms. American ControlConferences,2000:1551-1555.
[76] Anca D Hansen, Henrik Bindner and Anders Rebsdorf. Improving transition between poweroptimization and power limitation of variable speed variable pitch wind turbines. European WindEnergy Conference，Nice France，1-5March1999:889-892.
[77] E Bossanyi. Developments in individual blade pitch control. The Science of Making Torque fromWind. Delft University of Technology, The Netherlands, April19-212004.
[78] E. A. Bossanyi. Individual blade pitch control for load reduction. Wind Energy,2003,6:119–128.
[79] Kelouwani S., Agbossou K. Nonlinear model identification of wind turbine with a neural network.IEEE Transactionsion on Energy Conversion, Sept.2004:607-612.
[80] LARSEN J W. Nonlinear dynamics of wind turbine wings [D]. Aalborg: Aalborg University,2005.
[81] R. Hoffmann, P. Mustschler. The influence of control strategies on the energy capture of windturbines. IEEE Industry Applications Conference,2000:886-893.
[82]林勇刚，李伟，叶杭冶等.变速恒频风力机组变桨距控制系统[J].农业机械学报，2004，35(4):110-114．
[83]陈严,欧阳高飞,叶枝全.大型水平轴风力机传动系统的动力学研究.太阳能学报，2003,24(5)：729-734.
[84]Thomas A, Lennart S. Wind energy technology and current status. Review renewable andsustainable energy reviews,2000,32(4):315-374.
[85]钱翼翟.空气动力学.北京：北京航空航天大学出版社，2005.
[86] Leithead W, Connor. Control of variable speed wind turbines: dynamic models. InternationalJournal of Control,2000,73(13):1173-1189.
[87] Eric van der Hooft, P.Schaak. Wind turbine control algorithms. Energy Research Center of theNetherlands,2003.
[88]Tony B, David S, Nick J, et al. Wind energy. Berlin: Springer-Verlag Berlin Heidelberg,2007.181-199.
[89]Leith D J, Leithead W E. Implementation of wind turbine controllers. Journal of Electronics andControl,1997,66(3):349-380.
[90]张雷，李海东，李建林，等.基于LQR方法的风电机组变桨距控制的动态建模与仿真分析[J].太阳能学报，2008，29(7)：781-785.
[91] Muhando E.B，Senjyu T，Urasaki N，et al．Online WTG dynamic performance and transientstability enhancement by evolutionary LQG．IEEE Power Engineering Society General Meeting,2007. Tampa, FL,24-28June2007.
[92] Muhando E.B, Senjyu T, Zachary Siagi. Intelligent optimal control of wind power generatingsystem by a complemented linear quadratic gaussian approach．IEEE PES Power Africa2007Conference and Exposition Johannesburg, South Africa,16-20July2007.
[93] Pournaras C,Riziotis V,Kladas A. Wind turbine control strategy enabling mechanical stressreduction based on dynamic model including blade oscillation effects. Proceedings of the2008International Conference on Electrical Machines,Vilamoura,6-9Sept2008.
[94]梅生伟,申铁龙,刘康志.现代鲁棒控制理论与应用[M].北京:清华大学出版社,2003.
[95]郭庆鼎，蓝益鹏.永磁直线伺服电机L2鲁棒控制的研究[J].中国电机工程学报,2005,25(18)：146-151.
[96]金石,孙宜标,王成元.数控转台直接驱动伺服系统的L2鲁棒定位控制[J].电机与控制学报，2009，13(1)：83-87.
[97]蓝益鹏，郭庆鼎.永磁直线伺服系统H∞鲁棒控制[J].沈阳工业大学学报，2004，26(3)：281-283.
[98]林飞，张春朋，宋文超等.感应电机的L2增益鲁棒控制[J].中国电机工程学报，2003，23(9)：117-119.
[99]王江，李韬，曾启明.基于神经网络的同步电动机励磁反步控制[J].中国电机工程学报，2003，23(12)：140-145.
[100]孙宜标，郭庆鼎.基于滑模观测器的直线伺服系统反馈线性化速度跟踪控制[J].控制理论与应用，2004，21(3)：391-396.
[101]陈维，王耀南.基于神经网络的现代感应电机自适应L2鲁棒控制[J].中国电机工程学报．2007，27(15)：93-99.
[102] Schaft van der, A.J.L2-gain analysis of nonlinear systems and nonlinear state-feedback H∞control[J]. IEEE Transactions on Automatic Control,1992.37(6):770-784.
[103]Arjan van der aschaft.L2-gain and passivity techniques in nonlinear control[M].London：Springer-Verlag London Limited，2000.
[104]曲永印，赵希梅，郭庆鼎等.永磁同步电动机伺服系统自校正零相位误差跟踪控制[J].电工技术学报，2008，23(1)：60-64.
[105]侯忠生.非参数模型及其自适应控制理论[M].北京：科学出版社，1999：102-115.
[106]侯忠生.无模型自适应控制的现状和展望[J].控制理论与应用，2006,23(4)：586-592.
[107]韩志刚.无模型控制方法在化肥生产中的应用[J].控制理论与应用，2004，21(6)：858-863.
[108]韩志刚，汪国强.无模型控制律串级形式及其应用[J].自动化学报，200632(3)：345-352.
[109]韩志刚，杨艳梅.多输入多输出非线性系统的无模型控制律[J].黑龙江大学自然科学学报，1995，12(2)：1-7.
[110]秦滨，韩志刚.MIMO非线性系统的直接自适应控制[J].控制理论与应用，1997，14(1)：131-133.
[111]韩志刚，蒋爱萍，汪国强.无模型控制方法对多变量耦合系统控制的应用研究[J].控制与决策，2004，19(10)：1155-1162.
[112]韩志刚，蒋爱平，汪国强.合成氨生产中的氢氮比控制系统[J].控制理论与应用，2005，22(5)：762-766.
[113]马洁，陈智勇，侯忠生.大型舰船综合减遥系统无模型自适应控制[J].控制理论与应用，2009，26(11)：56-60.
[114]张日东.非线性预测控制及应用研究.浙江大学，2007.
[115]陈薇.非线性预测控制快速算法的研究与应用.中国科学技术大学，2007.
[116]林勇刚，李伟，崔宝玲.基于SVR风力机变桨距双模型切换预测控制.机械工程学报，2006(42)8：101-106.
[117]张新房.大型风力发电机组的智能控制研究.华北电力大学，2004.
[118]Ekelund T. Dynamics and control of structural loads of wind turbines. Proceedings of theAmerican Control Conference,1998:1720-1724.
[119]Ekelund T. Yaw control for reduction of structural dynamic loads in wind turbines. Journal ofWind Engineering and Industrial Aerodynamics,2000,85:241-262.
[120]Ervin B. Further load reductions with individual pitch control. Wind Energy,2005,8:481-485.
[121]Ervin B. Individual blade pitch control for load reduction. Wind Energy,2003,6:119-128.
[122]Burton Tony, Sharpe David, Jenkins Niek. Wind energy handbook. New York: John Wiley&Sons, Ltd,2001.
[123]M. Rossetti, E.A. Bossanyi. Damping of tower motions via pitch control–theory and practice.Proceedings of European Wind Energy Conference,2004.
[124]Kausihan Selvam. Individual pitch control for large scale wind turbines. Energy Research Centerof the Netherlands,2007.
[125]叶杭冶，潘东浩．风电机组变速与变距控制过程中的动力学问题研究．太阳能学报，2007，28(12)：1321-1328．
[126]Eric van der Hooft, P.Schaak. Wind turbine control algorithms. Energy Research Center of theNetherlands,2003.
[127]Ruben P, Daniel S. Integer variable structure controllers for small wind energy systems. Proc ofthe IEEE Canadian Conf on Elec and Computer Engineering.1999:1067-1072.
[128]Selvam K, Kanev S, van Wingerden J, et al. Feedback feed forward individual pitch control forwind turbine load reduction. International Journal of Robust and Nonlinear Control,2008,19:72-91.
[129]Selvam K. Individual pitch control for large scale wind turbine. Dissertation of master degree.Delft: Delft University of Technology,2007.13-18.
[130]林勇刚，李伟，陈晓波等.大型风力发电机组独立桨叶控制系统.太阳能学报，2005，26(6)：780-786.
[131]郭洪澈.兆瓦级风电机组独立变桨控制技术研究：（博士学位论文）.沈阳：沈阳工业大学，2008.
[132]林勇刚.大型风力机变桨距控制技术研究：（博士学位论文）.杭州：浙江大学，2005.
[133] DDOLAN D S L,LEHN P W.Simulation model of wind turbine3p torque oscillations due towind shear and tower shadow[J]．IEEE Transactions on Energy Conversion,2006,21(3):717-724.
[134] MICHAEL HUGHES F,ANAYA-LARA O,RAMTHARANG,et al.Influence of tower shadowand wind turbulence on the performance of power system stabilizers for DFIG-based windfarms[J].IEEE Transactions on Energy Conversion,2008,23(2):519-528.
[135] FADAEINEDJAD R,MOSCHOPOULOS G,MOALLEM M.The impact of tower shadow,yawerror,and wind shears on power quality in a wind-diesel system[J].IEEE Transactions on EnergyConversion,2009,24(1):102-111.
[136] EGGERS A J,DIGUMARTHI R,CHANEY K.Wind shear and turbulence effects on rotor fatigueand loads control[J].ASME Journal of Solar Energy Engineering.2003,125(4):402-409.
[2]2012年中国风电设备行业分析及市场研究报告.
[3]秦海岩.2009中国风电发展. http://wenku.baidu.com/view/9e4f5d563c1ec5da50e27040.html
[4]陈雷,邢作霞,潘建等.大型风力发电机组技术发展趋势.可再生能源,2003,(1):27-30.
[5]张新房.风力发电技术的发展及若干问题.现代电力，2003，20(5)：29-34.
[6]谢鲁冰，张振华，武国洪.直驱与双馈风机技术流派对比分析.应用能源技术，2012，176(8)：42-44.
[7]国家发展与改革委员会.能源发展“十一五”规划，2007.
[8]我国政策推动风电设备自主创新.中国投资咨询网，2008,5.
[9]范万新，苏志.国内外风能开发利用的现状和发展趋势.大众科技，2009，118(6)：131-133.
[10]张洋,李强,张晓东.风力发电机组控制技术综述.水利电力机械,2007,(7)：53-55.
[11]邓英，梁晶晶，王湘明等.减缓风力发电机组驱动链载荷的控制器.太阳能学报，2009，30(10)：1420-1423．
[12]刘颖明.永磁直驱风电机组控制技术研究：（博士学位论文）.沈阳：沈阳工业大学，2010.
[13]高指林.风力发电机组变桨距控制系统及其执行机构的研究：(硕士学位论文).武汉：武汉理工大学,2007.
[14]刑作霞.大型变速变距风力发电机组的柔性协调控制技术研究：(博士学位论文).北京：北京交通大学,2008.
[15]刘忠明，段守敏，王长路.风力发电齿轮箱设计制造技术的发展与展望.机械传动，2006，30（6）：1-6.
[16] E.Muljadi, C.P. Butterfield. Pitch-controlled variable-speed wind turbine generation. IEEETransactions on Industrial Applications,2001,37(1):240-246.
[17] N.Horiuchi, T. Kawahito. Torque and power limitations of variable speed wind turbines using pitchcontrol and generator power control. IEEE Power Engineering Society Summer Meeting，2001，1:638-643.
[18] W. L. Chen, Y. Y. Hsu. Unified voltage and pitch angle controller for wind-driven inductiongenerator system. IEEE Transactions on Aerospace and Electronic Systems.2008,44(3):913-926.
[19]高文元,祝振敏,井明波等.风电机组变桨距系统神经网络模糊自适应控制.武汉理工大学学报,2008,30(4)：533-536.
[20]王哲.大型风电机组变桨距控制策略研究：（博士学位论文）.沈阳：沈阳工业大学，2010.
[21]风电设备制造产业及公司分析.http://finance.sina.com.cn/stock/hyyj/20070202/14083307932.shtml.
[22]姚兴佳，宋俊等.风力发电机组原理与应用.北京：机械工业出版社，2009.
[23]叶杭冶.风电机组的控制技术.北京：机械工业出版社，2002.
[24]姚兴佳，刘国喜，朱家玲等.可再生能源及其发电技术.北京：科学出版社，2010.
[25]熊礼俭.风力发电新技术与发电工程设计、运行、维护及标准规范实用手册.北京：中国科学文化出版社，2005.
[26]Burton Tony, Sharpe David, Jenkins Niek. Wind energy handbook. New York: John Wiley&Sons,Ltd,2001.
[27]孟克其劳，陈虎，钱春震等.永磁直驱风力发电系统最大功率追踪策略研究.电力系统保护与控制，2012，40(22)：83-87.
[28]柳明，柳文.基于风速和空气密度估计的最大风能捕获.电网技术，2009，33(1)：56-60.
[29]王新生，吴吟箫，何川.基于风速预测的最大风能追踪控制系统仿真.电机与控制学报，2010，14(2)：20-24.
[30]刘姝，姚兴佳，王晓东等.模糊专家控制系统的最大风能追踪.微特电机，2012，40(9)：20-24.
[31]刘吉宏，吕跃刚，郭鹏等.风电系统最大风能追踪的智能模型预测控制.计算机工程与应用，2011，47(9)：228-232.
[32]赵亮，吕剑虹，向文国.采用极值搜索法的风电机组最大风能追踪控制.电网技术，2011，35(5)：171-175.
[33]付光杰，崔海龙，冉璇等.永磁同步风力发电机侧变流器控制策略.吉林大学学报，2011，29(5)：228-232.
[34]李游，成怡.直驱型永磁风力发电机的最大风能捕获影响因素分析.天津大学学报，2012，40(5)：70-74.
[35]汤天浩，陈新红，彭东恺等.直驱式永磁同步风力发电机稳态模型与最大功率跟踪控制.电源学报，2011，35(5)：11-15.
[36]殷明慧，张小莲，叶星等.一种基于收缩跟踪区间的改进最大功率点跟踪控制.中国电机工程学报，2012，32(27)：24-28.
[37]李晶，葛敏.最大风能追踪模糊控制器的仿真设计.风机技术，2010，35(6)：11-15.
[38]张文娟，高勇，杨媛.基于风力机参数辨识的最大风能捕获.电网技术，2009，33(17)：152-156.
[39]赵林坤.变速恒频风力发电系统转速鲁棒控制方法研究.长沙：长沙理工大学，2009.
[40]吴东吉.变速恒频双馈发电系统解耦控制研究.兰州：兰州理工大学.2008.
[41]李琳.双馈风力发电机滑模控制策略的研究.哈尔滨工业大学，2009.9.
[42]孔屹刚，王志新．大型风电机组模糊滑模鲁棒控制器设计与仿真[J]．中国电机工程学报，2008，28(14):136-141.
[43] Ruben P, Daniel S. Integer variable structure controllers for small wind energy systems. Proc of theIEEE Canadian Conf on Elec and Computer Engineering.1999:1067-1072.
[44] Battista H D, Mantz R J. Sliding mode control of torque ripple in wind energy conversion systemswith slip power recovery. Proc of the24th Annual Conf of IEEE，1998:651-656.
[45] Battista, R.J. Mantz, C.F. Christiansen. Dynamical sliding mode power control of wind driveninduction generators. IEEE Transactions on Energy Conversion,2000,15(4):451-457.
[46]Connor B. LQG Control of a constant speed horizontal axis wind turbine. The3rd IEEE Conf.onControl Appl,1994:251-252.
[47]郑雪梅，李琳，徐殿国.双馈风力发电系统低电压过渡的高阶滑模控制仿真研究.中国电机工程学报，2009，27：178-183.
[48] Song Y D, et al, Variable speed control of wind turbines using nonlinear and adaptivealgorithms. Journal of Wind Engineering and Industrial Aerodynamics,2000,85:293-308.
[49] D. Song, B.Dhinakaran.Control of wind turbines using nonlinear algorithms. American ControlConferences,2000:1551-1555.
[50]Qi Wang, Xiaohu Chen, Yanchao Ji. Fuzzy-based active and reactive control for brushlessdoubly-fed wind power generator system, APCCAS2006, Singapore,848-851.
[51]Xingjia Yao, Yanjun Jing, Zuoxia Xing. Direct torque control of a doubly-fed wind generator basedon grey-fuzzy logic. Proceedings of the2007IEEE, International Conference on Mechatronics andAutomation, August5-8,2007, Harbin, China,3587-3592.
[52]高文元，祝振敏.基于模糊自适应控制的风电机组变桨距系统.工业科技，2008，37(4)：45-46.
[53]钟声.模糊控制在变桨距恒速恒频风力发电机中的应用.应用技术，2008，36(2)：41-43.
[54]张先勇，吴婕，杨金明等.额定风速以上风力发电机组的恒功率H∞鲁棒控制.控制理论与应用，2008，25(2)：321-328.
[55] Liebst B S.A Pitch control system for the kamewa wind turbine.Dynamic Systems, Measurementand Control,1985:47-52.
[56]杨俊华，吴捷，杨金明等.风力发电系统中的最优控制策略综述.微特电机，2004，22(3)：30-42.
[57]张雅楠.变桨距与智能控制在风电机组中的应用.沈阳：沈阳工业大学，2010.
[58]邓英，梁晶晶，王湘明等.减缓风力发电机组驱动链载荷的控制器.太阳能学报，2009，30(10)：1420-1423.
[59]于振燕，张玮，张立强.基于遗传算法PID的风力机变桨距系统电液伺服控制.西华大学学报，自然科学版，2007，26(4)：64-65.
[60]陈思哲，吴捷，姚国兴等.基于微分几何的风力发电机组恒功率控制.控制理论与应用，2008(25)，2：336-340.
[61]赵林坤.变速恒频风力发电系统转速鲁棒控制方法研究.长沙：长沙理工大学，2009.
[62]周培毅，张新燕，张华中.基于遗传算法与BP神经网的风力发电机齿轮箱故障诊断研究.华北电力技术，2010，(7)：6-11.
[63]赵卓鹏，贾石峰.基于Elman神经网络的风力发电机组齿轮箱故障诊断研究.伺服控制，2010，6：65-66.
[64]许凌峰，徐大平，等.基于神经网络的风力发电机组变桨距复合控制.华北电力大学学报，2009，36(1)：28-34.
[65] Ekelund T. Yaw control for reduction of structural dynamic loads in wind turbines. Wind Eng. Ind.Aerodyn.,2000,:241-262.
[66]张玉华，李振凯.基于模糊控制的风力发电系统变桨距控制器的设计.现代电力，2007(24)6：58-61.
[67]郭鹏.风电机组非线性前馈与模糊PID结合变桨距控制研究.动力工程学报，2010(30)11：838-843.
[68]邢作霞，郑琼林.基于BP神经网络的PID变桨距风电机组控制.沈阳工业大学学报，2006，28(6)：681-686.
[69]师彪，李郁侠，于新花等.基于弹性自适应人工鱼群-BP神经网络的风轮节距控制环.农业工程学报，2010，26(1)：145-149.
[70] Shuhui Li, Wunsch D.C, OHair E.A. Using neural networks to estimate wind turbine powergeneration. IEEE Transactionsion on Energy Conversion,2001.
[71] Shi KL, Li H. A novel control of a small wind turbine driven generator based on neural networks.Piscataway NJ. Power Engineering Society General Meeting,2004,2:166-169.
[72] Murdoch A. Control design and performance analysis of a6mw wind turbine-generator. IEEETrans. PAS,1983:1340-1347.
[73] Ekelund T. Dynamics and control of structural loads of wind turbines. Proc of the AmericanControl Conf., Pennsylvania,1998.6:1720-1724.
[74] E.A.Bossanyi. Adaptive pitch control for a250kw wind turbine. Proc British Wind EnergyConference.1986:85-92.
[75] YD. Song, B.Dhinakaran.Control of wind turbines using nonlinear algorithms. American ControlConferences,2000:1551-1555.
[76] Anca D Hansen, Henrik Bindner and Anders Rebsdorf. Improving transition between poweroptimization and power limitation of variable speed variable pitch wind turbines. European WindEnergy Conference，Nice France，1-5March1999:889-892.
[77] E Bossanyi. Developments in individual blade pitch control. The Science of Making Torque fromWind. Delft University of Technology, The Netherlands, April19-212004.
[78] E. A. Bossanyi. Individual blade pitch control for load reduction. Wind Energy,2003,6:119–128.
[79] Kelouwani S., Agbossou K. Nonlinear model identification of wind turbine with a neural network.IEEE Transactionsion on Energy Conversion, Sept.2004:607-612.
[80] LARSEN J W. Nonlinear dynamics of wind turbine wings [D]. Aalborg: Aalborg University,2005.
[81] R. Hoffmann, P. Mustschler. The influence of control strategies on the energy capture of windturbines. IEEE Industry Applications Conference,2000:886-893.
[82]林勇刚，李伟，叶杭冶等.变速恒频风力机组变桨距控制系统[J].农业机械学报，2004，35(4):110-114．
[83]陈严,欧阳高飞,叶枝全.大型水平轴风力机传动系统的动力学研究.太阳能学报，2003,24(5)：729-734.
[84]Thomas A, Lennart S. Wind energy technology and current status. Review renewable andsustainable energy reviews,2000,32(4):315-374.
[85]钱翼翟.空气动力学.北京：北京航空航天大学出版社，2005.
[86] Leithead W, Connor. Control of variable speed wind turbines: dynamic models. InternationalJournal of Control,2000,73(13):1173-1189.
[87] Eric van der Hooft, P.Schaak. Wind turbine control algorithms. Energy Research Center of theNetherlands,2003.
[88]Tony B, David S, Nick J, et al. Wind energy. Berlin: Springer-Verlag Berlin Heidelberg,2007.181-199.
[89]Leith D J, Leithead W E. Implementation of wind turbine controllers. Journal of Electronics andControl,1997,66(3):349-380.
[90]张雷，李海东，李建林，等.基于LQR方法的风电机组变桨距控制的动态建模与仿真分析[J].太阳能学报，2008，29(7)：781-785.
[91] Muhando E.B，Senjyu T，Urasaki N，et al．Online WTG dynamic performance and transientstability enhancement by evolutionary LQG．IEEE Power Engineering Society General Meeting,2007. Tampa, FL,24-28June2007.
[92] Muhando E.B, Senjyu T, Zachary Siagi. Intelligent optimal control of wind power generatingsystem by a complemented linear quadratic gaussian approach．IEEE PES Power Africa2007Conference and Exposition Johannesburg, South Africa,16-20July2007.
[93] Pournaras C,Riziotis V,Kladas A. Wind turbine control strategy enabling mechanical stressreduction based on dynamic model including blade oscillation effects. Proceedings of the2008International Conference on Electrical Machines,Vilamoura,6-9Sept2008.
[94]梅生伟,申铁龙,刘康志.现代鲁棒控制理论与应用[M].北京:清华大学出版社,2003.
[95]郭庆鼎，蓝益鹏.永磁直线伺服电机L2鲁棒控制的研究[J].中国电机工程学报,2005,25(18)：146-151.
[96]金石,孙宜标,王成元.数控转台直接驱动伺服系统的L2鲁棒定位控制[J].电机与控制学报，2009，13(1)：83-87.
[97]蓝益鹏，郭庆鼎.永磁直线伺服系统H∞鲁棒控制[J].沈阳工业大学学报，2004，26(3)：281-283.
[98]林飞，张春朋，宋文超等.感应电机的L2增益鲁棒控制[J].中国电机工程学报，2003，23(9)：117-119.
[99]王江，李韬，曾启明.基于神经网络的同步电动机励磁反步控制[J].中国电机工程学报，2003，23(12)：140-145.
[100]孙宜标，郭庆鼎.基于滑模观测器的直线伺服系统反馈线性化速度跟踪控制[J].控制理论与应用，2004，21(3)：391-396.
[101]陈维，王耀南.基于神经网络的现代感应电机自适应L2鲁棒控制[J].中国电机工程学报．2007，27(15)：93-99.
[102] Schaft van der, A.J.L2-gain analysis of nonlinear systems and nonlinear state-feedback H∞control[J]. IEEE Transactions on Automatic Control,1992.37(6):770-784.
[103]Arjan van der aschaft.L2-gain and passivity techniques in nonlinear control[M].London：Springer-Verlag London Limited，2000.
[104]曲永印，赵希梅，郭庆鼎等.永磁同步电动机伺服系统自校正零相位误差跟踪控制[J].电工技术学报，2008，23(1)：60-64.
[105]侯忠生.非参数模型及其自适应控制理论[M].北京：科学出版社，1999：102-115.
[106]侯忠生.无模型自适应控制的现状和展望[J].控制理论与应用，2006,23(4)：586-592.
[107]韩志刚.无模型控制方法在化肥生产中的应用[J].控制理论与应用，2004，21(6)：858-863.
[108]韩志刚，汪国强.无模型控制律串级形式及其应用[J].自动化学报，200632(3)：345-352.
[109]韩志刚，杨艳梅.多输入多输出非线性系统的无模型控制律[J].黑龙江大学自然科学学报，1995，12(2)：1-7.
[110]秦滨，韩志刚.MIMO非线性系统的直接自适应控制[J].控制理论与应用，1997，14(1)：131-133.
[111]韩志刚，蒋爱萍，汪国强.无模型控制方法对多变量耦合系统控制的应用研究[J].控制与决策，2004，19(10)：1155-1162.
[112]韩志刚，蒋爱平，汪国强.合成氨生产中的氢氮比控制系统[J].控制理论与应用，2005，22(5)：762-766.
[113]马洁，陈智勇，侯忠生.大型舰船综合减遥系统无模型自适应控制[J].控制理论与应用，2009，26(11)：56-60.
[114]张日东.非线性预测控制及应用研究.浙江大学，2007.
[115]陈薇.非线性预测控制快速算法的研究与应用.中国科学技术大学，2007.
[116]林勇刚，李伟，崔宝玲.基于SVR风力机变桨距双模型切换预测控制.机械工程学报，2006(42)8：101-106.
[117]张新房.大型风力发电机组的智能控制研究.华北电力大学，2004.
[118]Ekelund T. Dynamics and control of structural loads of wind turbines. Proceedings of theAmerican Control Conference,1998:1720-1724.
[119]Ekelund T. Yaw control for reduction of structural dynamic loads in wind turbines. Journal ofWind Engineering and Industrial Aerodynamics,2000,85:241-262.
[120]Ervin B. Further load reductions with individual pitch control. Wind Energy,2005,8:481-485.
[121]Ervin B. Individual blade pitch control for load reduction. Wind Energy,2003,6:119-128.
[122]Burton Tony, Sharpe David, Jenkins Niek. Wind energy handbook. New York: John Wiley&Sons, Ltd,2001.
[123]M. Rossetti, E.A. Bossanyi. Damping of tower motions via pitch control–theory and practice.Proceedings of European Wind Energy Conference,2004.
[124]Kausihan Selvam. Individual pitch control for large scale wind turbines. Energy Research Centerof the Netherlands,2007.
[125]叶杭冶，潘东浩．风电机组变速与变距控制过程中的动力学问题研究．太阳能学报，2007，28(12)：1321-1328．
[126]Eric van der Hooft, P.Schaak. Wind turbine control algorithms. Energy Research Center of theNetherlands,2003.
[127]Ruben P, Daniel S. Integer variable structure controllers for small wind energy systems. Proc ofthe IEEE Canadian Conf on Elec and Computer Engineering.1999:1067-1072.
[128]Selvam K, Kanev S, van Wingerden J, et al. Feedback feed forward individual pitch control forwind turbine load reduction. International Journal of Robust and Nonlinear Control,2008,19:72-91.
[129]Selvam K. Individual pitch control for large scale wind turbine. Dissertation of master degree.Delft: Delft University of Technology,2007.13-18.
[130]林勇刚，李伟，陈晓波等.大型风力发电机组独立桨叶控制系统.太阳能学报，2005，26(6)：780-786.
[131]郭洪澈.兆瓦级风电机组独立变桨控制技术研究：（博士学位论文）.沈阳：沈阳工业大学，2008.
[132]林勇刚.大型风力机变桨距控制技术研究：（博士学位论文）.杭州：浙江大学，2005.
[133] DDOLAN D S L,LEHN P W.Simulation model of wind turbine3p torque oscillations due towind shear and tower shadow[J]．IEEE Transactions on Energy Conversion,2006,21(3):717-724.
[134] MICHAEL HUGHES F,ANAYA-LARA O,RAMTHARANG,et al.Influence of tower shadowand wind turbulence on the performance of power system stabilizers for DFIG-based windfarms[J].IEEE Transactions on Energy Conversion,2008,23(2):519-528.
[135] FADAEINEDJAD R,MOSCHOPOULOS G,MOALLEM M.The impact of tower shadow,yawerror,and wind shears on power quality in a wind-diesel system[J].IEEE Transactions on EnergyConversion,2009,24(1):102-111.
[136] EGGERS A J,DIGUMARTHI R,CHANEY K.Wind shear and turbulence effects on rotor fatigueand loads control[J].ASME Journal of Solar Energy Engineering.2003,125(4):402-409.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |