覆带起重机起升系统双马达同步控制技术研究
|
摘要
液压起升系统是履带起重机最重要的组成部分，它的安全性及稳定性直接关系到整机的工作性能，也是评价一台起重机性能优劣的重要指标。为了保证工作的可靠性，大型履带起重机常常采用单钩双卷扬的起升结构，即由两个结构、参数相同的液压马达共同提升同一个吊钩，完成对重物的起吊工作。但由于液压波动、系统泄漏，外部干扰等因素的影响，常常出现同步误差，如何保证履带起重机双卷扬系统的同步控制精度是摆在研究人员面前的首要问题。
就目前液压同步控制方法而言，大多数现有的控制方法往往过于复杂，或者是附加条件过多，并带有一定针对性，在应用上受到很大的局限。因此，本文从简便实用的观点出发，结合校企合作项目对450t履带起重机做了大量的分析与研究工作。研究的目的就是为了寻求一种合适的控制规律，使双马达同步控制系统得到较高的同步控制精度。
本文主要研究工作如下：
1、在建立系统数学模型的基础上，对液压起升系统及其关键元件的结构和原理进行深入研究，并通过传递函数法对系统的动态特性进行分析，找出影响双马达同步控制精度的相关因素。
针对平衡阀阀口通流面积梯度对平衡阀动态特性的影响，提出一种新的平衡阀阀口结构形式，以改善阀口通流面积梯度的突变对液压波动的影响；同时采取优化平衡阀和马达压力切断阀的结构参数等措施，降低系统压力波动的幅度，以减少压力波动对同步控制精度的影响。仿真和实验结果证明，优化设计方案有效，可行。
2、寻求一种新型的同步控制方法是本文的核心内容。神经网络具有自学习功能，不需要对被控对象进行精确的辨识和建模，就可以用简单的方法实现对复杂系统的有效控制。本文创新性地将神经网络智能控制策略应用于履带起重机的双卷扬控制系统中，并把单神经元控制与传统PID控制相结合，提出一种单神经元PID控制策略。把神经元的连接权重分别与PID三个控制参数相对应，可以实时对其进行调节，克服了传统PID控制参数不能在线自动整定的不足，从而适应实际工作过程中环境的不断变化。
3、依靠神经网络自学习、自适应功能，采用有监督Delta学习规则，按差值最小准则连续地对连接强度进行修正，使期望输出和实际输出的差值与两个神经元之间连接权值的变化量成正比，有效地加快收敛速度，具有控制简单，容易实现、鲁棒性强，同步控制精度高等优点。
4、单神经元控制是通过对连接权重进行调整的一个非线性优化调节过程，即权值是以系统的误差函数相应于其负梯度方向来进行自动调节的。所以，本文采用广义Lyapounoy非线性稳定性理论对单神经元PID控制系统进行稳定性分析，总结出提高系统稳定性的方法，即尽量使学习速率ηi取小值，以提高系统的稳定性。采用这种方法不必求解系统的微分方程，就可以进行稳定性判别，简单、可靠。
5、提出一种交叉耦合同步控制方式用于履带起重机双卷扬系统中，在两个子系统的输出量都作为反馈信号的同时，把输出量的差值也作为一个附加的反馈信号进行跟踪比较，最终实现同步控制的目的。这种控制方式较同等方式和主从方式相比，具有更快的收敛速度，并能很好的适应负载变化，具有较高的同步控制精度。
6、为了验证理论分析的正确性，以及采用控制策略的合理性，应用AMESim软件与Matlab/Simulink软件进行联合仿真。并把传统PID控制和单神经元PID控制效果进行对比，得出最终结论，即：单神经元PID的控制性能优于传统PID控制，更具智能性。本文所提出的控制策略基本符合最初设计目的，为液压同步控制提供了新的思路。
Hydraulic lifting system is a most important part of crawler crane, itssecurity, stability and handling performance is directly related to the machine'sperformance, it is also an important indicator of the performance merits of theevaluation of a crane. In order to ensure the reliability of the work, a largecrawler crane is often used single hook dual winch lifting structure consists oftwo structures, the same parameters of the hydraulic motor upgrade with ahook to complete the lifting of heavy objects. However, due to hydraulicfluctuations, the system leakage and external interference factors there areoften the synchronization error, how to ensure the synchronization controlaccuracy of the double-winch system to become the most important issuebefore the designer
However, hydraulic synchronization control methods, most of the existingcontrol methods are often too complex or too many conditions attached, withsome targeted and significant limitations on the application. Therefore, startingfrom the simple and practical point of view, the combination of analysis andresearch work done a lot of school-enterprise cooperation project of 450tcrawler crane, the purpose of the study is to find a suitable control law,dual-motor synchronous control to obtain a higher synchronization accuracy.
The main work is as follows:
1. The system mathematical model based on the structure and principlesof the hydraulic lifting system and its key components in-depth study andanalysis on the dynamic characteristics of the system transfer function, find outthe impact of dual motor synchronous control The accuracy of the relevantfactors.
Gradient balancing valve dynamic characteristics of the flow area for thebalance valve valve port, put forward a new kind of balance valve valve port structure to improve the valve port through flow area gradient mutations affectthe hydraulic fluctuations; taken to optimize the balance valve and motorpressure shut-off valve structure parameters and other measures to reduce thevolatility of the system pressure in order to reduce pressure fluctuations in thesynchronization control accuracy. Proved through simulation analysis andexperimental studies to optimize the design of the program is effective andfeasible.
2. To seek a new type of synchronization control method is the corecontent of this article. The neural network has the accurate identification andmodeling of self-learning function, does not require the controlled object, youcan use a simple method to achieve effective control of complex systems. Thisinnovation to single-neuron intelligent control strategy applied to crawlercranes, dual hoist control system and neural network control with conventionalPID control the combination, for a single neuron PID control strategy. Neuronconnection weights to three and PID control parameters corresponding to thereal-time be adjusted to overcome the traditional PID control parameters cannot be on-line automatic tuning deficiencies, and thus adapt to the changingenvironment in the actual work process.
3. Relying on self-learning neural network, adaptive function, the use ofsupervision Delta learning rule, the difference between the minimum criteria forcontinuous correction of the connection strength, so that the differencebetween the desired output and actual output and the connection weightsbetween two neurons the change is proportional to the amount of effectivelyspeed up the convergence, with a simple control and easy to implement,robust and strong, synchronized control of high precision.
4. The single neuron control is to optimize the adjustment process througha non-linear adjustment of connection weights, the weights are the errorfunction corresponding to its negative gradient direction to automatically adjust.Therefore, the the generalized Lyapounoy nonlinear stability theory for stabilityanalysis of single neuron PID control system, summed up the method to improve system stability, that is, as far as possible, the learning rate to take asmall value in order to improve system stability. Using this method do not haveto solve the system of differential equations, stability of discrimination, simple,reliable.
5. Cross-coupling synchronization control for crawler crane winch systemin two subsystems of the output as the feedback signal at the same time, thedifference between the two output as an additional feedback signal trackingeventually achieve the synchronization control purposes. This control methodthan the same manner as compared to the master-slave mode, with a fasterconvergence speed, and are well suited to the load changes, has a highsynchronization control accuracy.
6. In order to verify the theoretical analysis of the correctness of rationality,and control strategy of the AMESim software and MATLAB / Simulink softwareco-simulation, and the traditional PID control and the single neuron PID controltwo control strategies compared and concluded a final conclusion, that thesingle neuron PID control on the control performance is much better thantraditional PID control, more intelligent. That the proposed control strategy inline with the initial design purpose, it provides a new thinking of hydraulicsynchronization control.
就目前液压同步控制方法而言，大多数现有的控制方法往往过于复杂，或者是附加条件过多，并带有一定针对性，在应用上受到很大的局限。因此，本文从简便实用的观点出发，结合校企合作项目对450t履带起重机做了大量的分析与研究工作。研究的目的就是为了寻求一种合适的控制规律，使双马达同步控制系统得到较高的同步控制精度。
本文主要研究工作如下：
1、在建立系统数学模型的基础上，对液压起升系统及其关键元件的结构和原理进行深入研究，并通过传递函数法对系统的动态特性进行分析，找出影响双马达同步控制精度的相关因素。
针对平衡阀阀口通流面积梯度对平衡阀动态特性的影响，提出一种新的平衡阀阀口结构形式，以改善阀口通流面积梯度的突变对液压波动的影响；同时采取优化平衡阀和马达压力切断阀的结构参数等措施，降低系统压力波动的幅度，以减少压力波动对同步控制精度的影响。仿真和实验结果证明，优化设计方案有效，可行。
2、寻求一种新型的同步控制方法是本文的核心内容。神经网络具有自学习功能，不需要对被控对象进行精确的辨识和建模，就可以用简单的方法实现对复杂系统的有效控制。本文创新性地将神经网络智能控制策略应用于履带起重机的双卷扬控制系统中，并把单神经元控制与传统PID控制相结合，提出一种单神经元PID控制策略。把神经元的连接权重分别与PID三个控制参数相对应，可以实时对其进行调节，克服了传统PID控制参数不能在线自动整定的不足，从而适应实际工作过程中环境的不断变化。
3、依靠神经网络自学习、自适应功能，采用有监督Delta学习规则，按差值最小准则连续地对连接强度进行修正，使期望输出和实际输出的差值与两个神经元之间连接权值的变化量成正比，有效地加快收敛速度，具有控制简单，容易实现、鲁棒性强，同步控制精度高等优点。
4、单神经元控制是通过对连接权重进行调整的一个非线性优化调节过程，即权值是以系统的误差函数相应于其负梯度方向来进行自动调节的。所以，本文采用广义Lyapounoy非线性稳定性理论对单神经元PID控制系统进行稳定性分析，总结出提高系统稳定性的方法，即尽量使学习速率ηi取小值，以提高系统的稳定性。采用这种方法不必求解系统的微分方程，就可以进行稳定性判别，简单、可靠。
5、提出一种交叉耦合同步控制方式用于履带起重机双卷扬系统中，在两个子系统的输出量都作为反馈信号的同时，把输出量的差值也作为一个附加的反馈信号进行跟踪比较，最终实现同步控制的目的。这种控制方式较同等方式和主从方式相比，具有更快的收敛速度，并能很好的适应负载变化，具有较高的同步控制精度。
6、为了验证理论分析的正确性，以及采用控制策略的合理性，应用AMESim软件与Matlab/Simulink软件进行联合仿真。并把传统PID控制和单神经元PID控制效果进行对比，得出最终结论，即：单神经元PID的控制性能优于传统PID控制，更具智能性。本文所提出的控制策略基本符合最初设计目的，为液压同步控制提供了新的思路。
Hydraulic lifting system is a most important part of crawler crane, itssecurity, stability and handling performance is directly related to the machine'sperformance, it is also an important indicator of the performance merits of theevaluation of a crane. In order to ensure the reliability of the work, a largecrawler crane is often used single hook dual winch lifting structure consists oftwo structures, the same parameters of the hydraulic motor upgrade with ahook to complete the lifting of heavy objects. However, due to hydraulicfluctuations, the system leakage and external interference factors there areoften the synchronization error, how to ensure the synchronization controlaccuracy of the double-winch system to become the most important issuebefore the designer
However, hydraulic synchronization control methods, most of the existingcontrol methods are often too complex or too many conditions attached, withsome targeted and significant limitations on the application. Therefore, startingfrom the simple and practical point of view, the combination of analysis andresearch work done a lot of school-enterprise cooperation project of 450tcrawler crane, the purpose of the study is to find a suitable control law,dual-motor synchronous control to obtain a higher synchronization accuracy.
The main work is as follows:
1. The system mathematical model based on the structure and principlesof the hydraulic lifting system and its key components in-depth study andanalysis on the dynamic characteristics of the system transfer function, find outthe impact of dual motor synchronous control The accuracy of the relevantfactors.
Gradient balancing valve dynamic characteristics of the flow area for thebalance valve valve port, put forward a new kind of balance valve valve port structure to improve the valve port through flow area gradient mutations affectthe hydraulic fluctuations; taken to optimize the balance valve and motorpressure shut-off valve structure parameters and other measures to reduce thevolatility of the system pressure in order to reduce pressure fluctuations in thesynchronization control accuracy. Proved through simulation analysis andexperimental studies to optimize the design of the program is effective andfeasible.
2. To seek a new type of synchronization control method is the corecontent of this article. The neural network has the accurate identification andmodeling of self-learning function, does not require the controlled object, youcan use a simple method to achieve effective control of complex systems. Thisinnovation to single-neuron intelligent control strategy applied to crawlercranes, dual hoist control system and neural network control with conventionalPID control the combination, for a single neuron PID control strategy. Neuronconnection weights to three and PID control parameters corresponding to thereal-time be adjusted to overcome the traditional PID control parameters cannot be on-line automatic tuning deficiencies, and thus adapt to the changingenvironment in the actual work process.
3. Relying on self-learning neural network, adaptive function, the use ofsupervision Delta learning rule, the difference between the minimum criteria forcontinuous correction of the connection strength, so that the differencebetween the desired output and actual output and the connection weightsbetween two neurons the change is proportional to the amount of effectivelyspeed up the convergence, with a simple control and easy to implement,robust and strong, synchronized control of high precision.
4. The single neuron control is to optimize the adjustment process througha non-linear adjustment of connection weights, the weights are the errorfunction corresponding to its negative gradient direction to automatically adjust.Therefore, the the generalized Lyapounoy nonlinear stability theory for stabilityanalysis of single neuron PID control system, summed up the method to improve system stability, that is, as far as possible, the learning rate to take asmall value in order to improve system stability. Using this method do not haveto solve the system of differential equations, stability of discrimination, simple,reliable.
5. Cross-coupling synchronization control for crawler crane winch systemin two subsystems of the output as the feedback signal at the same time, thedifference between the two output as an additional feedback signal trackingeventually achieve the synchronization control purposes. This control methodthan the same manner as compared to the master-slave mode, with a fasterconvergence speed, and are well suited to the load changes, has a highsynchronization control accuracy.
6. In order to verify the theoretical analysis of the correctness of rationality,and control strategy of the AMESim software and MATLAB / Simulink softwareco-simulation, and the traditional PID control and the single neuron PID controltwo control strategies compared and concluded a final conclusion, that thesingle neuron PID control on the control performance is much better thantraditional PID control, more intelligent. That the proposed control strategy inline with the initial design purpose, it provides a new thinking of hydraulicsynchronization control.
引文
[1]周红.履带起重机双卷扬单钩的一种控制同步技术[J].建设机械技术与管理,2007(6):84-85.
[2]钮汉忠,许明恒,陈留.伸缩臂铁路起重机的单钩双卷扬液压驱动系统[J].起重运输机械,1994(11):22-24.
[3]刘晓峰,刘昕晖,王龙山等.基于模糊PID控制的大型履带起重机双马达速度同步控制[J].吉林大学学报.2011, 41(3): 659-664.
[4]刘金江.履带起重机产品现状及发展趋势[J].建筑机械,2009(5):32-34.
[5]王欣,高顺德.国外履带起重机的特点及国内市场现状[J].建筑机械,2006.13:12-16.
[6]王欣,屈福政.国外履带起重机的发展[J].起重运输机械,1999(2):1-3.
[7]王凌纹.履带起重机:迎接越来越大的挑战[J].建设机械技术与管理,2006(7):20-25.
[8]薛学伟.“中国制造”履带起重机登顶之路[J].建设机械技术与管理,2011(6) :88-89
[9]莫宇.中联重科ZCC3200NP型履带式起重机成功下线[J].今日工程机械,2011(11):47
[10]韩学松.中国工程机械行业变革与走势预测[J].工程机械与维修,2010(11):12-15.
[11]司宁博.核危机笼罩下的履带式起重机行业[J].工程机械与维修,式2011(5):45-48.
[12] Yagiz N,Ozbulur V.Sliding Mode Control of Active Suspensions.In:12thIEEE International Symposium on Intelligent Control,1997.373-378.
[13] FAVENNEC G,ALIRAND M,LEBRUN M.Optimal response of pressurereducer and stability influence of the downstream line dynamics[J].The 2ndFluid Power Net Int. PhD Symposium, Modena,Italy,2002(7):1-10.
[14]倪敬,项占琴,潘晓红等.双缸同步提升电液系统建模和控制[J].机械工程学报,2007.43(2):81-86.
[15] Byung-Young,Moon.Study of parameter identification using hybridneuralgenetic algorithm in electro-hydraulic servo system. Proceedings ofSPIE The International Society for Optical Engineering, 2005:156-162.
[16]谢岳,陈乐,孙坚.永磁同步电动机的自适应非线性轨迹跟踪控制[J].电工技术学报,2006.2l(1):82-85．
[17]李士勇.模糊控制、神经控制和智能控制论(第二版).哈尔滨:哈尔滨工业大学出版社,1998.
[18]李人厚.智能控制理论和方法.西安:西安电子科技大学出版社,1999.
[19] Y.Koren.Cross-coupled Biaxial Computer Controls for ManufacturingSystems.ASME Journal of Dynamic Systems[J].Measurement and Control,1980.102(2):256-272.
[20]韩波,王庆丰,路甬祥.电液比例位置同步控制系统的控制结构研究[J].机床与液压,1997(1):7-10.
[21]曹玲芝,李春文,牛超等.基于相邻交叉耦合的多感应电机滑模同步控制[J].电机与控制学报,2008.12(5):586-592.
[22] Dong Sun,Xiaoyin Shao,Gang Feng.A Model-Free Cross-Coupled Controlfor Position Synchronization of Multi-Axis Motions: Theory andExperiments. IEEE Transaction on Control Systems Technology,2007. 15(2):306-314.
[23]张庆年.前馈神经网络的特性分析与应用[J].武汉交通科技大学学报，1999.23(4):372-375.
[24] T.Kamano, N.Iuchi, M.Tomizuka. Adaptive Feedforward Controller forSynchronization of Two Axes Positioning System.Transactions of theSociety of Instrument and Control Engineers,1993.29(7):785-791.
[25] M.Tomizuka,T.Kamano.Synchronization of Two Motion Control Axes underAdaptive Feedforward Control.ASME Journal of Dynamic Systems,Measurement and Control,1992.114(2):196-203.
[26]赖锡坤,朱大奇,顾伟.基于滑模控制的双起升场桥双吊具同步控制[J].控制工程,2007.14(7):145-147.
[27]姚燕春.基于单神经元自适应控制的多电机同步控制系统的研究（D）.江苏.江苏大学电气信息工程学院.
[28] Hong Sun. George Chiu.Motion Synchronization for Multi CylinderElectro-Hydraulic System.2001 IEEE/ASME International ConferenceonAdvanced Intelligent Mechatronics Proceedings.Italy.2001.1(1):636-641.
[29] Zhou Di.H∞Synchronization Control of Linear Systems and Its Applicationto Wafer-retical Stage[J]. Chinese Journal of Mechanical Engineering, 2005.18(2): 174-178.
[30]王燕山,李运华,王益群.五轴电液仿真转台的双马达同步控制[J].北京航空航天大学学报,2008.34(4):408-411.
[31]吴保林,裘丽华等.单泵驱动双马达速度同步控制技术研究[J].系统仿真学报, 2006.18(6):1586-1588.
[32]翟大鹏.大型履带式起重机双卷扬同步控制系统研究[D].吉林.吉林大学机械科学与工程学院.2011.
[33] A.Angels, H.Nigmeijer. Synchronization of Robots via Estimated StateFeedback a Cooperative Approach.IEEE Transactions on Control SystemsTechnology,2004.12(4):542-554.
[34] Jiao Zongxia,Gao Junxia,Hua Qing et,al.The Velocity Synchronizing Controlon the Electro-Hydraulic Load Simulator.Chinese Journal of Aeronatics,2004.17(1):39-46.
[35] Yong Xiao, Kuanyi Zhu, Hwee Choo Liaw.Generalized synchronizationcontrol of multi-axis motion systems. Control Engineering Practice, 2005.13(7): 809-819.
[36]桂本,冯冬芹,褚健等.基于单神经元的网络同步补偿算法研究[J].仪器仪表学报,2006,27(12):1573-1577
[37]祝轩,侯榆青,路平立等.基于单神经元PID控制器的闭环控制系统[J].西北大学学报,2004.33(1):413-416.
[38] Santosh J V,Sreenatha A G,Chandrasekhar.Suppression of wing rock ofslender delta wings using a single neuron controller.IEEE Transac- tions onControl Systems Technology,1998.6(5):671-677.
[39]赵路.大型履带式起重机卷扬液压系统的动态特性研究[D].吉林.吉林大学机械科学与工程学院.2011.
[40]张克危.流体机械原理[M].北京:机械工业出版社,2001.
[41]路甬祥.液压气动技术手册[M].北京:机械工业出版社,2002.
[42]王益华,屈福正.泵控液压起升机构二次起升动态特性的仿真研究[J].工程机械,2006(11):8-12.
[43]王晋之,曹捷等.一种汽车起重机用液压变量马达的性能分析和优化设计[J].液压气动与密封,2008(5):33-37.
[44] LIN Z C,HUANG C J.Study of estimation of damping coefficient andangular displacement for air motor rotation experiment[J].Journal of theChinese Society of Mechanical Engineers,2008.29(4):271-280.
[45] AHN K W,HYUN J H.Optimization of double loop control parameters for avariable displacement hydraulic motor by genetic algorithms[J]. JSME,International Journal Series C-Mechanical Systems Machine Elements andManufacturing,2005.48(1):81-86.
[46] QU J Y,REN C B,et al.Parameters optimization method for variabledisplacement pump/motor and transmission of hydraulic braking energyregeneration system[J].International Forum on Computer ScienceTechnology and Applications,2009.3:19-22.
[47]潘权,颜荣庆,李自光等.新型液压平衡阀动态特性研究[J].长沙交通学院学报,2003,19(3):19-23.
[48]李锋,马长林.平衡阀动态特性仿真与参数优化研究[J].机床与液压, 2003(4):232-233.
[49] Muhammad M R, Jose L F P. Numerical simulation and animation ofoscillating turbulent flow in a counterbalance valve[C].Energy Conver- sionEngineering Conference,Proceedings of the 32nd Intersociety. Honolulu.HI.USA,1997. 2:1525-1530.
[50]顾银芳,苑士华,安永江.仿真技术的发展与展望[J].河北工业科技,2000(5)：36-39.
[51] DORF R C, BISHOP R H.Modern control systems[M].Beijing:Science Press,2002.
[52]侯琳.多学科领域复杂系统仿真平台[J].CAD/CAE与制造业信息化,2005.12:56-69.
[53]付永领,祁晓野.AMESim系统建模和仿真—从入门到精通[M].北京:北京航空航天大学出版社,2006.
[54]余佑官,龚国芳,胡国良.AMESim仿真技术及其在液压系统中的应用[J].液压气动与密封,2005(3):100-104.
[55]李瑾,邓卫华.AMESim与MATLAB/Simulink联合仿真技术应用[J].情报指挥控制系统与仿真技术,2004.10:67-70.
[56]韩守习,张大可.基于SIMULINK的起重机起升机构动态仿真[J].重庆建筑大学学报,2003.25(6):67-73.
[57]陶建峰,王旭永,刘成良,朱野.负载变形敏感双马达同步驱动系统建模与仿真[J].系统仿真学报,2007.19(7):1574-1578.
[58]刘能宏,田树军.液压系统动态特性数字仿真[M].大连:大连理工大学出版社,1993.
[59]林贵瑜,董永平,李伟涛.履带起重机变幅机构动态特性分析[J].建筑机械化,2009(11).
[60] Choi S B, Choi Y T, Park D W.A sliding mode control of a full carelectrorheological suspension system via hardware in-the-loop Simulation[J].ASME Journal of dynamic systems, measurements and control, 2000. 122(3):114-121.
[61]吴卫峰.液压系统液压脉动研究[J].浙江工业大学学报,2005(6):696-701.
[62]孔晓武.带长管道的负载敏感系统研究[D].浙江.浙江大学机械与能源学院,2003.
[63] Alleyne A, Hedrick J K. Nonlinear adaptive control of active suspen-sions.IEEE Transactions on Control Systems Technology,1995.3(1): 94-101.
[64] Z.Towarek.The dynamic stability of a crane standing on soil during therotation of the boom[J].Int.J.Mech,1998.40(6):557-574.
[65] Favennec G,Alirand M.Optimal response of pressure reducer and stabilityinfluence of the downstream line dynamics[J].Modena,Italy, 2002(7):1-10.
[66] Liu X F,Liu X H H,Wang L S.The Simulation Analysis and ExperimentalResearch on Pressure Oscillation of Crane Hoisting System[C].InternationalConference on Electrical and Control Engineering. Wuhan,China,June, 2010:2432–2435.
[67] ZHAO L,LIU X H,WANG T J.Influence of counterbalance valve parameterson stability of the crane lifting system[C].International Conference onMechatronics and Automation, Xi’an, China,2010: 1010-1014.
[68]黄黎芹,刘荣,陈鹰.阀控液压位置伺服系统管路压力冲击研究[J].机电工程,2009.26(3):80-83.
[69] Jing Wang,Guo Fanggong.Hua Yongyang.Control of Bulk Modulus of Oil inHydraulie SystCms.Proceedings of the 2008 IEEE/ASME,2008(2): 1390-1395.
[70]阮晓芳,邱敏秀,孔晓武.蓄能器对带长管道阀控系统动态特性的改善[J].工程设计,2002.9(2):97-100.
[71]孔晓武,邱敏秀,魏建华,吴根茂.带长管道的阀控系统动态特性研究[J].中国机械工程,2002.13 (7):1141-1143.
[72]田勇,李建生,曹宪周等.管道效应对液压同步系统动态特性的影响研究[J].机床与液压,2009.37(9):93-96.
[73] HUANG Li-qin,LIU Rong,CHEN Ying.Research on pipeline pressure shockin valve control hydraulic positioning system.Mechanical & ElectricalEngineering Magazine,2009.22(3):234-236.
[74]孙增圻.智能理论与技术[M].北京:清华大学出版社,107-123.
[75] Piazzi, Aurelio. A noncausal approach for PID control[J].Journal of ProcessControl,2006(16):831-843.
[76] S.Daley, Liu G P. Optimal PID Tuning Using Direct Search Algorithms[J].Computing & Control,1999.10(2):51-57.
[77] Liu Hongling.Design of PID parameters self-tuning fuzzy control system andits application in hydroelectric system[J].WSEAS Transactions on Circuitsand Systems,2006(5):646-651.
[78]金耀.自适应单神经元智能控制策略及其在汽车主动悬架中的应用研究
[D].湖南.湖南大学机械与汽车工程学院.2007.
[79]徐中,孙伟,刘晓冰.单神经元自适应PID控制器的研究[J].大连理工大学学报,1999.39(5):667-672.
[80] Chen C T,Yen C H.Multivariable process control using decentralized singleneuron controllers.Journal of Chemical Engineering of Japan,1998.31(1):14-20.
[81] Leonid Reznik,Omar Ghanayem,Anna Bourmistrov.PID Plus Fuzzy Contro-ller Structures as a Design Base for Industrial Applications[J].En gineeringapplications of artificial intelligence,2000.13:419-430.
[82]张世杰,曹喜滨.基于单神经元自适应PID控制的航天器大角度姿态机[J]，上海航天,2003.6:9-14.
[83]刘宇,刘杰,戴丽等.基于神经网络和PID算法的数控机床并行混合控制模型[J].信息与控制,2006.35(1):30-42.
[84]袁野,仲崇权,田中旭.一种基于单神经元的机器人实时控制自适应算法研究[J].小型微型计算机系统,2003.124(12):312-314.
[85]王宁,张建明,王树青.增益模糊自整定的增量式神经元非模型控制及其应用[J].模式识别与人工智能,2000.13(3):305-308.
[86] S.Guo,L.Huang. Periodic oscillation for discrete-time Hopfield neuralnetworks [J].Physics Lettesr A,2004.329(3):199-206.
[87]张忠,李传东.具有时变时滞的递归神经网络的渐近稳定性分析[J].计算机研究与发展,2007.44(6):973-979.
[88]吴佑寿,赵明生.激活函数可调的神经元模型及其有监督学习与应用[J].中国科学E辑,2001.31(3):263-272.
[89]赵锡龄,焦云婷.单神经元自适应控制器PID在再热汽温控制中的应用[J].中国电机工程学报,2001.21(2):93-96.
[90]付兴武,赵克定,刘庆和.双马达同步驱动系统自适应神经元网络控制.哈尔滨工业大学学报,1999.31(5):111-117.
[91] Lu Ren,James K. Mills,Dong Sun. Adaptive Synchronized Control for aPlanar Parallel Manipulator: Theory and Experiments, 2006. 128(4):976-979.
[92] Q.Zhang,R.Ma, J.xu. Stability of cellular neural networks with delay[J].Electronics Letters, 2001.37(9):575-576.
[93] K.Hirasawa,S.Mabu,J.Hu.Propagation and control of stochastic signalsthrough universal learning networks[J].Neural Networks, 2006. 19(4):487-499.
[94] Di Zhou,Tielong Shen,Katsutoshi Tamura.Adaptive Nonlinear Synch-ronization Control of Twin-Gyro Precession.Journal of Dynamic Systems,Measurement and Control,2006.128(3):592-599.
[95] Y.Xia,J.Wang.A discrete-time recurrent neural network for shortest Pathrouting[C].Automatic Control,IEEE Transactions on,2000.45(11):2129-2134.
[96]罗艳蕾.液压同步回路及同步控制系统实现的方法[J].液压与气动, 2004(4):84-88.
[97]刘一江,易理刚,童桦.电液伺服试验系统多变量控制的新方法[J].电工技术学报,2003.18(6)48-52.
[98] Ji Hong,FuXin.Investigation inio cavitation induced noise within Hydraulicrelief valve.Tetsuhiro Tsukiji, Proceedings of Interna- tional Symposium onFluid Power,Japan 2002:409-412.
[99] Wen-pei,Ming-hsiang.Time domain system identification of unknown initialconditions.Journal of Zhejiang University Science,2004.5: 1035-1044.
[100] Zhou Jicheng,Zhang Lixun,Wang Anmin.Control Strategy of the Synchro-drive Electro-hydraulic Servo System.Proceedings of the 2nd Inter- nationalSymposium on Fluid Power Transmission and Control.1995: 365-367.
[101]涂江涛,黄明辉,刘忠伟.运用AMESim/Simulink的液压机同步平衡控制系统的仿真研究[J].现代制造工程,2009(2):36-39.
[102]王欣,杜汉平,滕儒民.基于刚柔耦合的履带起重机虚拟样机建模技术[J].中国工程机械学报,2007(01).
[103]齐晓慧,田庆民,董海瑞.基于Matlab系统辨识工具箱的系统建模[J].兵工自动化,2006.25(10):88-90.
[104] Jiao Liangzhen ,FU Yongzheng.The experiment study of flow property andthe formula simulation about the SPF balance valve.Valves,2006 (2):100-104.
[105]刘春芳,周璐,吴盛林.基于解耦控制的双电液伺服系统同步技术研究[J].机床与液压,2007(2):181-183.
[106] D.A.Badley,D.W.Seward.The development control and operation of anautonomous robotic excavator[J].Journal of Intelligent and Robotic Systems,1998.21:73-97.
[107] K. Sato,Y.Sakawa.Modelling and control of a flexible rotary crane [J]. Int.J.Control,1988(3):208-210.
[108] FAVENNEC G,ALIRAND M, LEBRUN M. Optimal response of pressurereducer and stability influence of the downstream line dynamics[J].The 2ndFluid Power Net Int. PhD Symposium, Modena,Italy,July 2002:1-10.
[109] Osman Balci,Richard E N.The simulation model development environ- mentan overview[J].Winter Simulation Conf,1992:726-736.
[110] D.A.Badley,D.W.Seward.The development,control and operation of anautonomous robotic excavator.Journal of Intelligent and Robotic Systems,1998.21:73–97.
[111]李军伟,赵克定.协调控制同步策略在液压仿真转台中的应用[J].系统仿真学报,2005.17(7):1645-1647.
[112] Lorenz R D and Schmidt P B.Sychronized Motion Control for ProcessAutomation.Proceeding of 1989 Industry Applications Annual Meeting,1989:1693-1698.
[113] Eduardo Torres, Mario Garcia Sanz.Experimental Results of the VariableSpeed,Direct Drive Multipole Synchronous Wind Turbine TWT1650.WindEnergy,2004.7(2):109-118.
[114]苏永清,甭蕴诗.模糊自适应再负载仿真台同步补偿中的应用研究[J].机械工程学报,2001.37(7):15-17.
[115] Sun Dong,Shao Xiaoyin and Gang Feng. A Model-Free Cross-CoupledControl[J].Position Synchronization of Multi-Axis Motions.Theory andExperiments.IEEE Transactions on control systems technology, 2007.15(2):306-314.
[116]逄波,王占林,白国长.工程机械液压底盘试验台双马达同步的研究[J].系统仿真学报,2007.19(9):2018-2021.
[117] D.Yue,J.Fang,S.Won.Delay-dependent robust stability of stochasticuncertain systems with time delay and markovian jump parameters[J].Circuits Systems Signal Processing,2003.22(4):351-365.
[118]李厦,乌建中.模糊Petri网在液压同步提升系统故障诊断中的应用[J].中国工程机械学报,2006.4(1):68-71.
[119] Oded Yaniv.Quantitative Feedback Design of Linear and Nonlinear ControlSystems[J].Massachusetts: Kluwer Academic Publishers, 1999. 29:139-140.
[120] Eduard Eitelberg.Quantitative Feedback Design for Tracking ErrorTolerance[J]. Automatic, 2000.36(2):319-326.
[121] E.Boje,I.Horowitz,E.Eitelberg.Application of Quantitative Feed- backTheory to a System with Time Delay and Paremeter Uncertainty.Transections of South African Institute of Electrical Engineers, 1986.77(2):179-185.
[122] P.S.V.Nataraj,Sachin Tharewal.An Interval Analysis Algorithm forAutomated Controller Synthesis in QFT Designs[J].Journal of DynamicSystems, Measurement and Control.2007.129(3):311-321.
[123] O.Yaniv,M.Nagurka.Automatic Loop Shaping of Structured ControllersSatisfying QFT Performance[J].Jouranl of Dynamic Systems.Measurementand Control,2005.17(3):472-477.
[124] M.Garcia Sanz,J.X.Ostolaza.QFT Control of a Biological Reactor forSimultaneous Ammonia and Nitrates Removal[J].Systems AnalysisModelling Simulation,2000.38(2):353-370.
[125]王铠,王占林,付永领,李万国.电液仿真转台控制系统设计与仿真研究[J].宇航学报,2007.28(1):178-182.
[126] W.Wu,S.Javasuriya. A QFT Design Methodology for Feedback SystemsWith Input Rate or Amplitude and Rate Saturation.Proceedings of theAmerican Control Conference,2001(1):376-383.
[127]胡建军.电液比例同步控制系统建模及控制策略研究[D].云南.昆明理工大学机械电子工程.2008.
[128]郭庆鼎,唐光谱,唐元钢,傅建国.基于自适应控制的双电机同步传动控制技术的研究[J].机械工程学报,2002.38(2):79-81.
[129] Ke Li,Jian Chen,Ziyuan Xiao,Mingqian Xu.An Electro-hydraulic System forSynchronized Roof Erection.Automation in Construction, 2003(12):29-42.
[130] Yang Huayong, Shi Hu, Gong Guofang, Hu Guoliang.Electro-hydraulicProportional Control of Thrust System for Shield Tunneling Machine[J].Automation in Construction,2009(18):950-956.
[2]钮汉忠,许明恒,陈留.伸缩臂铁路起重机的单钩双卷扬液压驱动系统[J].起重运输机械,1994(11):22-24.
[3]刘晓峰,刘昕晖,王龙山等.基于模糊PID控制的大型履带起重机双马达速度同步控制[J].吉林大学学报.2011, 41(3): 659-664.
[4]刘金江.履带起重机产品现状及发展趋势[J].建筑机械,2009(5):32-34.
[5]王欣,高顺德.国外履带起重机的特点及国内市场现状[J].建筑机械,2006.13:12-16.
[6]王欣,屈福政.国外履带起重机的发展[J].起重运输机械,1999(2):1-3.
[7]王凌纹.履带起重机:迎接越来越大的挑战[J].建设机械技术与管理,2006(7):20-25.
[8]薛学伟.“中国制造”履带起重机登顶之路[J].建设机械技术与管理,2011(6) :88-89
[9]莫宇.中联重科ZCC3200NP型履带式起重机成功下线[J].今日工程机械,2011(11):47
[10]韩学松.中国工程机械行业变革与走势预测[J].工程机械与维修,2010(11):12-15.
[11]司宁博.核危机笼罩下的履带式起重机行业[J].工程机械与维修,式2011(5):45-48.
[12] Yagiz N,Ozbulur V.Sliding Mode Control of Active Suspensions.In:12thIEEE International Symposium on Intelligent Control,1997.373-378.
[13] FAVENNEC G,ALIRAND M,LEBRUN M.Optimal response of pressurereducer and stability influence of the downstream line dynamics[J].The 2ndFluid Power Net Int. PhD Symposium, Modena,Italy,2002(7):1-10.
[14]倪敬,项占琴,潘晓红等.双缸同步提升电液系统建模和控制[J].机械工程学报,2007.43(2):81-86.
[15] Byung-Young,Moon.Study of parameter identification using hybridneuralgenetic algorithm in electro-hydraulic servo system. Proceedings ofSPIE The International Society for Optical Engineering, 2005:156-162.
[16]谢岳,陈乐,孙坚.永磁同步电动机的自适应非线性轨迹跟踪控制[J].电工技术学报,2006.2l(1):82-85．
[17]李士勇.模糊控制、神经控制和智能控制论(第二版).哈尔滨:哈尔滨工业大学出版社,1998.
[18]李人厚.智能控制理论和方法.西安:西安电子科技大学出版社,1999.
[19] Y.Koren.Cross-coupled Biaxial Computer Controls for ManufacturingSystems.ASME Journal of Dynamic Systems[J].Measurement and Control,1980.102(2):256-272.
[20]韩波,王庆丰,路甬祥.电液比例位置同步控制系统的控制结构研究[J].机床与液压,1997(1):7-10.
[21]曹玲芝,李春文,牛超等.基于相邻交叉耦合的多感应电机滑模同步控制[J].电机与控制学报,2008.12(5):586-592.
[22] Dong Sun,Xiaoyin Shao,Gang Feng.A Model-Free Cross-Coupled Controlfor Position Synchronization of Multi-Axis Motions: Theory andExperiments. IEEE Transaction on Control Systems Technology,2007. 15(2):306-314.
[23]张庆年.前馈神经网络的特性分析与应用[J].武汉交通科技大学学报，1999.23(4):372-375.
[24] T.Kamano, N.Iuchi, M.Tomizuka. Adaptive Feedforward Controller forSynchronization of Two Axes Positioning System.Transactions of theSociety of Instrument and Control Engineers,1993.29(7):785-791.
[25] M.Tomizuka,T.Kamano.Synchronization of Two Motion Control Axes underAdaptive Feedforward Control.ASME Journal of Dynamic Systems,Measurement and Control,1992.114(2):196-203.
[26]赖锡坤,朱大奇,顾伟.基于滑模控制的双起升场桥双吊具同步控制[J].控制工程,2007.14(7):145-147.
[27]姚燕春.基于单神经元自适应控制的多电机同步控制系统的研究（D）.江苏.江苏大学电气信息工程学院.
[28] Hong Sun. George Chiu.Motion Synchronization for Multi CylinderElectro-Hydraulic System.2001 IEEE/ASME International ConferenceonAdvanced Intelligent Mechatronics Proceedings.Italy.2001.1(1):636-641.
[29] Zhou Di.H∞Synchronization Control of Linear Systems and Its Applicationto Wafer-retical Stage[J]. Chinese Journal of Mechanical Engineering, 2005.18(2): 174-178.
[30]王燕山,李运华,王益群.五轴电液仿真转台的双马达同步控制[J].北京航空航天大学学报,2008.34(4):408-411.
[31]吴保林,裘丽华等.单泵驱动双马达速度同步控制技术研究[J].系统仿真学报, 2006.18(6):1586-1588.
[32]翟大鹏.大型履带式起重机双卷扬同步控制系统研究[D].吉林.吉林大学机械科学与工程学院.2011.
[33] A.Angels, H.Nigmeijer. Synchronization of Robots via Estimated StateFeedback a Cooperative Approach.IEEE Transactions on Control SystemsTechnology,2004.12(4):542-554.
[34] Jiao Zongxia,Gao Junxia,Hua Qing et,al.The Velocity Synchronizing Controlon the Electro-Hydraulic Load Simulator.Chinese Journal of Aeronatics,2004.17(1):39-46.
[35] Yong Xiao, Kuanyi Zhu, Hwee Choo Liaw.Generalized synchronizationcontrol of multi-axis motion systems. Control Engineering Practice, 2005.13(7): 809-819.
[36]桂本,冯冬芹,褚健等.基于单神经元的网络同步补偿算法研究[J].仪器仪表学报,2006,27(12):1573-1577
[37]祝轩,侯榆青,路平立等.基于单神经元PID控制器的闭环控制系统[J].西北大学学报,2004.33(1):413-416.
[38] Santosh J V,Sreenatha A G,Chandrasekhar.Suppression of wing rock ofslender delta wings using a single neuron controller.IEEE Transac- tions onControl Systems Technology,1998.6(5):671-677.
[39]赵路.大型履带式起重机卷扬液压系统的动态特性研究[D].吉林.吉林大学机械科学与工程学院.2011.
[40]张克危.流体机械原理[M].北京:机械工业出版社,2001.
[41]路甬祥.液压气动技术手册[M].北京:机械工业出版社,2002.
[42]王益华,屈福正.泵控液压起升机构二次起升动态特性的仿真研究[J].工程机械,2006(11):8-12.
[43]王晋之,曹捷等.一种汽车起重机用液压变量马达的性能分析和优化设计[J].液压气动与密封,2008(5):33-37.
[44] LIN Z C,HUANG C J.Study of estimation of damping coefficient andangular displacement for air motor rotation experiment[J].Journal of theChinese Society of Mechanical Engineers,2008.29(4):271-280.
[45] AHN K W,HYUN J H.Optimization of double loop control parameters for avariable displacement hydraulic motor by genetic algorithms[J]. JSME,International Journal Series C-Mechanical Systems Machine Elements andManufacturing,2005.48(1):81-86.
[46] QU J Y,REN C B,et al.Parameters optimization method for variabledisplacement pump/motor and transmission of hydraulic braking energyregeneration system[J].International Forum on Computer ScienceTechnology and Applications,2009.3:19-22.
[47]潘权,颜荣庆,李自光等.新型液压平衡阀动态特性研究[J].长沙交通学院学报,2003,19(3):19-23.
[48]李锋,马长林.平衡阀动态特性仿真与参数优化研究[J].机床与液压, 2003(4):232-233.
[49] Muhammad M R, Jose L F P. Numerical simulation and animation ofoscillating turbulent flow in a counterbalance valve[C].Energy Conver- sionEngineering Conference,Proceedings of the 32nd Intersociety. Honolulu.HI.USA,1997. 2:1525-1530.
[50]顾银芳,苑士华,安永江.仿真技术的发展与展望[J].河北工业科技,2000(5)：36-39.
[51] DORF R C, BISHOP R H.Modern control systems[M].Beijing:Science Press,2002.
[52]侯琳.多学科领域复杂系统仿真平台[J].CAD/CAE与制造业信息化,2005.12:56-69.
[53]付永领,祁晓野.AMESim系统建模和仿真—从入门到精通[M].北京:北京航空航天大学出版社,2006.
[54]余佑官,龚国芳,胡国良.AMESim仿真技术及其在液压系统中的应用[J].液压气动与密封,2005(3):100-104.
[55]李瑾,邓卫华.AMESim与MATLAB/Simulink联合仿真技术应用[J].情报指挥控制系统与仿真技术,2004.10:67-70.
[56]韩守习,张大可.基于SIMULINK的起重机起升机构动态仿真[J].重庆建筑大学学报,2003.25(6):67-73.
[57]陶建峰,王旭永,刘成良,朱野.负载变形敏感双马达同步驱动系统建模与仿真[J].系统仿真学报,2007.19(7):1574-1578.
[58]刘能宏,田树军.液压系统动态特性数字仿真[M].大连:大连理工大学出版社,1993.
[59]林贵瑜,董永平,李伟涛.履带起重机变幅机构动态特性分析[J].建筑机械化,2009(11).
[60] Choi S B, Choi Y T, Park D W.A sliding mode control of a full carelectrorheological suspension system via hardware in-the-loop Simulation[J].ASME Journal of dynamic systems, measurements and control, 2000. 122(3):114-121.
[61]吴卫峰.液压系统液压脉动研究[J].浙江工业大学学报,2005(6):696-701.
[62]孔晓武.带长管道的负载敏感系统研究[D].浙江.浙江大学机械与能源学院,2003.
[63] Alleyne A, Hedrick J K. Nonlinear adaptive control of active suspen-sions.IEEE Transactions on Control Systems Technology,1995.3(1): 94-101.
[64] Z.Towarek.The dynamic stability of a crane standing on soil during therotation of the boom[J].Int.J.Mech,1998.40(6):557-574.
[65] Favennec G,Alirand M.Optimal response of pressure reducer and stabilityinfluence of the downstream line dynamics[J].Modena,Italy, 2002(7):1-10.
[66] Liu X F,Liu X H H,Wang L S.The Simulation Analysis and ExperimentalResearch on Pressure Oscillation of Crane Hoisting System[C].InternationalConference on Electrical and Control Engineering. Wuhan,China,June, 2010:2432–2435.
[67] ZHAO L,LIU X H,WANG T J.Influence of counterbalance valve parameterson stability of the crane lifting system[C].International Conference onMechatronics and Automation, Xi’an, China,2010: 1010-1014.
[68]黄黎芹,刘荣,陈鹰.阀控液压位置伺服系统管路压力冲击研究[J].机电工程,2009.26(3):80-83.
[69] Jing Wang,Guo Fanggong.Hua Yongyang.Control of Bulk Modulus of Oil inHydraulie SystCms.Proceedings of the 2008 IEEE/ASME,2008(2): 1390-1395.
[70]阮晓芳,邱敏秀,孔晓武.蓄能器对带长管道阀控系统动态特性的改善[J].工程设计,2002.9(2):97-100.
[71]孔晓武,邱敏秀,魏建华,吴根茂.带长管道的阀控系统动态特性研究[J].中国机械工程,2002.13 (7):1141-1143.
[72]田勇,李建生,曹宪周等.管道效应对液压同步系统动态特性的影响研究[J].机床与液压,2009.37(9):93-96.
[73] HUANG Li-qin,LIU Rong,CHEN Ying.Research on pipeline pressure shockin valve control hydraulic positioning system.Mechanical & ElectricalEngineering Magazine,2009.22(3):234-236.
[74]孙增圻.智能理论与技术[M].北京:清华大学出版社,107-123.
[75] Piazzi, Aurelio. A noncausal approach for PID control[J].Journal of ProcessControl,2006(16):831-843.
[76] S.Daley, Liu G P. Optimal PID Tuning Using Direct Search Algorithms[J].Computing & Control,1999.10(2):51-57.
[77] Liu Hongling.Design of PID parameters self-tuning fuzzy control system andits application in hydroelectric system[J].WSEAS Transactions on Circuitsand Systems,2006(5):646-651.
[78]金耀.自适应单神经元智能控制策略及其在汽车主动悬架中的应用研究
[D].湖南.湖南大学机械与汽车工程学院.2007.
[79]徐中,孙伟,刘晓冰.单神经元自适应PID控制器的研究[J].大连理工大学学报,1999.39(5):667-672.
[80] Chen C T,Yen C H.Multivariable process control using decentralized singleneuron controllers.Journal of Chemical Engineering of Japan,1998.31(1):14-20.
[81] Leonid Reznik,Omar Ghanayem,Anna Bourmistrov.PID Plus Fuzzy Contro-ller Structures as a Design Base for Industrial Applications[J].En gineeringapplications of artificial intelligence,2000.13:419-430.
[82]张世杰,曹喜滨.基于单神经元自适应PID控制的航天器大角度姿态机[J]，上海航天,2003.6:9-14.
[83]刘宇,刘杰,戴丽等.基于神经网络和PID算法的数控机床并行混合控制模型[J].信息与控制,2006.35(1):30-42.
[84]袁野,仲崇权,田中旭.一种基于单神经元的机器人实时控制自适应算法研究[J].小型微型计算机系统,2003.124(12):312-314.
[85]王宁,张建明,王树青.增益模糊自整定的增量式神经元非模型控制及其应用[J].模式识别与人工智能,2000.13(3):305-308.
[86] S.Guo,L.Huang. Periodic oscillation for discrete-time Hopfield neuralnetworks [J].Physics Lettesr A,2004.329(3):199-206.
[87]张忠,李传东.具有时变时滞的递归神经网络的渐近稳定性分析[J].计算机研究与发展,2007.44(6):973-979.
[88]吴佑寿,赵明生.激活函数可调的神经元模型及其有监督学习与应用[J].中国科学E辑,2001.31(3):263-272.
[89]赵锡龄,焦云婷.单神经元自适应控制器PID在再热汽温控制中的应用[J].中国电机工程学报,2001.21(2):93-96.
[90]付兴武,赵克定,刘庆和.双马达同步驱动系统自适应神经元网络控制.哈尔滨工业大学学报,1999.31(5):111-117.
[91] Lu Ren,James K. Mills,Dong Sun. Adaptive Synchronized Control for aPlanar Parallel Manipulator: Theory and Experiments, 2006. 128(4):976-979.
[92] Q.Zhang,R.Ma, J.xu. Stability of cellular neural networks with delay[J].Electronics Letters, 2001.37(9):575-576.
[93] K.Hirasawa,S.Mabu,J.Hu.Propagation and control of stochastic signalsthrough universal learning networks[J].Neural Networks, 2006. 19(4):487-499.
[94] Di Zhou,Tielong Shen,Katsutoshi Tamura.Adaptive Nonlinear Synch-ronization Control of Twin-Gyro Precession.Journal of Dynamic Systems,Measurement and Control,2006.128(3):592-599.
[95] Y.Xia,J.Wang.A discrete-time recurrent neural network for shortest Pathrouting[C].Automatic Control,IEEE Transactions on,2000.45(11):2129-2134.
[96]罗艳蕾.液压同步回路及同步控制系统实现的方法[J].液压与气动, 2004(4):84-88.
[97]刘一江,易理刚,童桦.电液伺服试验系统多变量控制的新方法[J].电工技术学报,2003.18(6)48-52.
[98] Ji Hong,FuXin.Investigation inio cavitation induced noise within Hydraulicrelief valve.Tetsuhiro Tsukiji, Proceedings of Interna- tional Symposium onFluid Power,Japan 2002:409-412.
[99] Wen-pei,Ming-hsiang.Time domain system identification of unknown initialconditions.Journal of Zhejiang University Science,2004.5: 1035-1044.
[100] Zhou Jicheng,Zhang Lixun,Wang Anmin.Control Strategy of the Synchro-drive Electro-hydraulic Servo System.Proceedings of the 2nd Inter- nationalSymposium on Fluid Power Transmission and Control.1995: 365-367.
[101]涂江涛,黄明辉,刘忠伟.运用AMESim/Simulink的液压机同步平衡控制系统的仿真研究[J].现代制造工程,2009(2):36-39.
[102]王欣,杜汉平,滕儒民.基于刚柔耦合的履带起重机虚拟样机建模技术[J].中国工程机械学报,2007(01).
[103]齐晓慧,田庆民,董海瑞.基于Matlab系统辨识工具箱的系统建模[J].兵工自动化,2006.25(10):88-90.
[104] Jiao Liangzhen ,FU Yongzheng.The experiment study of flow property andthe formula simulation about the SPF balance valve.Valves,2006 (2):100-104.
[105]刘春芳,周璐,吴盛林.基于解耦控制的双电液伺服系统同步技术研究[J].机床与液压,2007(2):181-183.
[106] D.A.Badley,D.W.Seward.The development control and operation of anautonomous robotic excavator[J].Journal of Intelligent and Robotic Systems,1998.21:73-97.
[107] K. Sato,Y.Sakawa.Modelling and control of a flexible rotary crane [J]. Int.J.Control,1988(3):208-210.
[108] FAVENNEC G,ALIRAND M, LEBRUN M. Optimal response of pressurereducer and stability influence of the downstream line dynamics[J].The 2ndFluid Power Net Int. PhD Symposium, Modena,Italy,July 2002:1-10.
[109] Osman Balci,Richard E N.The simulation model development environ- mentan overview[J].Winter Simulation Conf,1992:726-736.
[110] D.A.Badley,D.W.Seward.The development,control and operation of anautonomous robotic excavator.Journal of Intelligent and Robotic Systems,1998.21:73–97.
[111]李军伟,赵克定.协调控制同步策略在液压仿真转台中的应用[J].系统仿真学报,2005.17(7):1645-1647.
[112] Lorenz R D and Schmidt P B.Sychronized Motion Control for ProcessAutomation.Proceeding of 1989 Industry Applications Annual Meeting,1989:1693-1698.
[113] Eduardo Torres, Mario Garcia Sanz.Experimental Results of the VariableSpeed,Direct Drive Multipole Synchronous Wind Turbine TWT1650.WindEnergy,2004.7(2):109-118.
[114]苏永清,甭蕴诗.模糊自适应再负载仿真台同步补偿中的应用研究[J].机械工程学报,2001.37(7):15-17.
[115] Sun Dong,Shao Xiaoyin and Gang Feng. A Model-Free Cross-CoupledControl[J].Position Synchronization of Multi-Axis Motions.Theory andExperiments.IEEE Transactions on control systems technology, 2007.15(2):306-314.
[116]逄波,王占林,白国长.工程机械液压底盘试验台双马达同步的研究[J].系统仿真学报,2007.19(9):2018-2021.
[117] D.Yue,J.Fang,S.Won.Delay-dependent robust stability of stochasticuncertain systems with time delay and markovian jump parameters[J].Circuits Systems Signal Processing,2003.22(4):351-365.
[118]李厦,乌建中.模糊Petri网在液压同步提升系统故障诊断中的应用[J].中国工程机械学报,2006.4(1):68-71.
[119] Oded Yaniv.Quantitative Feedback Design of Linear and Nonlinear ControlSystems[J].Massachusetts: Kluwer Academic Publishers, 1999. 29:139-140.
[120] Eduard Eitelberg.Quantitative Feedback Design for Tracking ErrorTolerance[J]. Automatic, 2000.36(2):319-326.
[121] E.Boje,I.Horowitz,E.Eitelberg.Application of Quantitative Feed- backTheory to a System with Time Delay and Paremeter Uncertainty.Transections of South African Institute of Electrical Engineers, 1986.77(2):179-185.
[122] P.S.V.Nataraj,Sachin Tharewal.An Interval Analysis Algorithm forAutomated Controller Synthesis in QFT Designs[J].Journal of DynamicSystems, Measurement and Control.2007.129(3):311-321.
[123] O.Yaniv,M.Nagurka.Automatic Loop Shaping of Structured ControllersSatisfying QFT Performance[J].Jouranl of Dynamic Systems.Measurementand Control,2005.17(3):472-477.
[124] M.Garcia Sanz,J.X.Ostolaza.QFT Control of a Biological Reactor forSimultaneous Ammonia and Nitrates Removal[J].Systems AnalysisModelling Simulation,2000.38(2):353-370.
[125]王铠,王占林,付永领,李万国.电液仿真转台控制系统设计与仿真研究[J].宇航学报,2007.28(1):178-182.
[126] W.Wu,S.Javasuriya. A QFT Design Methodology for Feedback SystemsWith Input Rate or Amplitude and Rate Saturation.Proceedings of theAmerican Control Conference,2001(1):376-383.
[127]胡建军.电液比例同步控制系统建模及控制策略研究[D].云南.昆明理工大学机械电子工程.2008.
[128]郭庆鼎,唐光谱,唐元钢,傅建国.基于自适应控制的双电机同步传动控制技术的研究[J].机械工程学报,2002.38(2):79-81.
[129] Ke Li,Jian Chen,Ziyuan Xiao,Mingqian Xu.An Electro-hydraulic System forSynchronized Roof Erection.Automation in Construction, 2003(12):29-42.
[130] Yang Huayong, Shi Hu, Gong Guofang, Hu Guoliang.Electro-hydraulicProportional Control of Thrust System for Shield Tunneling Machine[J].Automation in Construction,2009(18):950-956.
© 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 |