塔式起重机智能防摆和定位控制方法研究
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摘要
本论文在分析国内外塔式起重机的研究现状和发展趋势的基础上，针对其特点和目前控制方案中存在的不足，设计出应用于塔式起重机系统的定位和防摆控制的新方法，保障系统安全、快速、运行平稳，改善系统的动静态性能，提高系统运行效率，实现负载精确定位和快速消摆。主要研究内容如下：
首先，根据模糊滑模控制原理，设计了一种基于时滞滤波器的塔式起重机模糊滑模防摆控制新方法。运用滑模控制消除负载摆动，模糊控制对滑模趋近率参数进行调节，抑制了一般滑模控制的抖振现象，并利用时滞滤波器对模型输入进行滤波，消除不确定性系统的残留振动，在存在外部干扰的情况下,实现对小车的定位和负载摆动的有效控制，仿真结果表明方法的有效性和可行性。
其次，在普通滑模面的基础上设计出PD分数阶滑模面，分数阶滑模面的定义将使得系统具有较高的鲁棒性和快速性，它在消除了系统的高频抖振的同时，使得滑模运动状态保持一个较快的速度趋近至切换面。通过遗传算法对分数阶滑模控制器中的参数进行了优化,并取得较好的控制效果。
最后，通过对塔式起重机系统的动力学模型分析，针对塔式起重机模型参数的不确定性和在运行过程中存在的负载摆动，提出了一种神经网络滑模防摆控制新方法。利用神经网络输出逼近系统的不确定项，不需要对模型进行近似解耦或线性化处理，并且考虑了系统所受的摩擦力等因素，存在外界干扰的情况下，系统仍能实现对臂架小车的精确定位和减少负载的摆动时间，削弱了系统的高频抖振，提高了系统的控制性能。
Based on the analysis of the current research status and developmenttendency of crane indoors and outdoors, according to the characteristics of towercrane system and the disadvantages of the current control method, the newpositioning and anti-swing control is designed for the intelligent tower cranesystem so as to obtain the performances of absolute safety, fast speed andsmooth operation, improve the dynamic and static, increase system efficiency,and obtain precise positioning and quick anti-swing. The main contents are asfollows:
Firstly, based on time-delayed filter and the fuzzy sliding mode controltheory, a new method of fuzzy sliding mode anti-swing control is proposed fortower crane. This method, which consists the sliding mode control to eliminatethe load swing and the fuzzy control to adjust the parameters of reaching law,weakens or avoids the chattering and improves the rate when the system reachesthe sliding surface. And the time-delayed filter which could filter the modelinput signal is designed to reduce residual vibration in the uncertain system. Thismethod enables the system to have good dynamic performances and enhancesthe quality of control system. The simulation results show the feasibility andeffectiveness of the method.
Secondly, the PD fractional sliding surface on the basis of the commonsliding surface is designed, where the definition of fractional sliding surface hasa high robustness and fast speed so as to reduce the chattering phenomenon insliding mode control (SMC) and lead to maintain a faster speed to reach thesliding surface. Genetic algorithm is used to determine and optimize theparameters of fractional sliding mode controller (FSMC). The simulation resultsshow that the method obtains better control effect.
Finally, through the force analysis for tower crane system, a new neuralnetwork sliding mode control method is formulated for the uncertainties of cranemodel parameters. The neural network is adopted to approximate theuncertainties of system, and considering the friction of system, it is needless to approximately decouple or exactly linearize the model of tower crane, and thecontroller can accurately position the trolley, suppress the payload swing even inthe presence of parameters uncertainties and external disturbance and improvethe control performance of the system.
首先，根据模糊滑模控制原理，设计了一种基于时滞滤波器的塔式起重机模糊滑模防摆控制新方法。运用滑模控制消除负载摆动，模糊控制对滑模趋近率参数进行调节，抑制了一般滑模控制的抖振现象，并利用时滞滤波器对模型输入进行滤波，消除不确定性系统的残留振动，在存在外部干扰的情况下,实现对小车的定位和负载摆动的有效控制，仿真结果表明方法的有效性和可行性。
其次，在普通滑模面的基础上设计出PD分数阶滑模面，分数阶滑模面的定义将使得系统具有较高的鲁棒性和快速性，它在消除了系统的高频抖振的同时，使得滑模运动状态保持一个较快的速度趋近至切换面。通过遗传算法对分数阶滑模控制器中的参数进行了优化,并取得较好的控制效果。
最后，通过对塔式起重机系统的动力学模型分析，针对塔式起重机模型参数的不确定性和在运行过程中存在的负载摆动，提出了一种神经网络滑模防摆控制新方法。利用神经网络输出逼近系统的不确定项，不需要对模型进行近似解耦或线性化处理，并且考虑了系统所受的摩擦力等因素，存在外界干扰的情况下，系统仍能实现对臂架小车的精确定位和减少负载的摆动时间，削弱了系统的高频抖振，提高了系统的控制性能。
Based on the analysis of the current research status and developmenttendency of crane indoors and outdoors, according to the characteristics of towercrane system and the disadvantages of the current control method, the newpositioning and anti-swing control is designed for the intelligent tower cranesystem so as to obtain the performances of absolute safety, fast speed andsmooth operation, improve the dynamic and static, increase system efficiency,and obtain precise positioning and quick anti-swing. The main contents are asfollows:
Firstly, based on time-delayed filter and the fuzzy sliding mode controltheory, a new method of fuzzy sliding mode anti-swing control is proposed fortower crane. This method, which consists the sliding mode control to eliminatethe load swing and the fuzzy control to adjust the parameters of reaching law,weakens or avoids the chattering and improves the rate when the system reachesthe sliding surface. And the time-delayed filter which could filter the modelinput signal is designed to reduce residual vibration in the uncertain system. Thismethod enables the system to have good dynamic performances and enhancesthe quality of control system. The simulation results show the feasibility andeffectiveness of the method.
Secondly, the PD fractional sliding surface on the basis of the commonsliding surface is designed, where the definition of fractional sliding surface hasa high robustness and fast speed so as to reduce the chattering phenomenon insliding mode control (SMC) and lead to maintain a faster speed to reach thesliding surface. Genetic algorithm is used to determine and optimize theparameters of fractional sliding mode controller (FSMC). The simulation resultsshow that the method obtains better control effect.
Finally, through the force analysis for tower crane system, a new neuralnetwork sliding mode control method is formulated for the uncertainties of cranemodel parameters. The neural network is adopted to approximate theuncertainties of system, and considering the friction of system, it is needless to approximately decouple or exactly linearize the model of tower crane, and thecontroller can accurately position the trolley, suppress the payload swing even inthe presence of parameters uncertainties and external disturbance and improvethe control performance of the system.
引文
[1] Sung-Kun Cho, Ho-Hoon Lee. An Anti-Sway Control of3–Dimensional OverheadCrane[C]//Proceedings of the American Control Conference.2000,(6):1037-1041.
[2] Hanafy M.Onla. Control of Gantry and Tower Cranes[D]. Blacksburg, Virginia,Virginia Polytechnic Institute and State University,January,2003.
[3] Parker, G., Groom, K., Hurtado, J. E., Feddema, J., Robinett, R.,&Leban, F.Experimental verification of a command shaping boom crane control system[C]//InAmerican control conference,1999,(1):86-90.
[4] Al-mousa A.A., Nayfeh A.H., Kachroo P.. Control of rotary cranes using fuzzylogic[C]//Proceedings of18th Biennial Conference on Mechanical Vibration and Noise,DET Pittsburgh, PA, September2001:2535-2544.
[5] Omar H.M., Nayfeh A.H.. A simple adaptive feedback controller for towercranes[C]//Proceedings of18th Biennial Conference on Mechanical Vibration andNoise, Pittsburgh, PA, September2001:2611-2621.
[6] S.Chatterjee. Vibration control by recursive time-delayed acceleration feedback[J].Journal of Sound and Vibration,2008,(317):67-70.
[7] Kunihiko Nakazono. Vibration control of load for rotary crane system using neuralnetwork with GA-based training[J]. Artif Life Robotics,2008,(13):98-101.
[8] Jorg Neupert, Eckhard Arnold and Klaus Schneider, Tracking and anti-sway control forboom cranes[J]. Control Engineering Practice,2010,(18)1:31–44.
[9] David Blackburn, Jason Lawrence. Radial-motion assisted command shapers fornonlinear tower crane rotational slewing[J]. Control Engineering Practice,2010,(18):523-531.
[10]李伟.基于动态误差最小的起重机最优消摆控制[J].电气自动化,2002,5:8-12.
[11]李伟,吴志新,齐保良.塔式起重机载荷摆动模型[J].机械工程学报,1993,29(4):15-22.
[12]齐伯文等.塔式起重机智能控制系统的最优反馈控制[J].哈尔滨建筑工程学报,1995,28(1):90-94.
[13]董明晓,张素,宋传增.回转起重机的建模与控制[J].机电产品开发与创新,2005,18(1):106-108.
[14]王建南,刘德君.基于模糊自适应PID控制的吊车防摆定位系统[J].微计算机信息,2007,23(22):35-80.
[15]张晓华，贾智勇.基于输入整形策略的船上回转吊车防摆控制[J].控制工程,2008,15(3):245-249.
[16]林贵瑜，杨新顺等.塔式起重栅吊装物摆动的控制[J].建筑机械化,2006,(11):34-36.
[17]刘晓胜.塔机运行的关键控制算法研究[J].科学技术与工程,2010,10(2):1671-1815.
[18] Zhen Z M, Meng W J, Zhang J G, et al. Scheme of sliding mode control based onmodified particle swarm optimization[J]. Systems Engineering-Theory&Practice,2009,29(5):137-141
[19] Michael Basin, Dario Calderon-Alvarez. Sliding mode regulator as solution to optimalcontrol problem for non-linear polynomial systems[J]. Journal of the Franklin Institute.2010(347):910–922.
[20]刘金坤.滑模变结构控制MATLAB仿真[M].北京:清华大学出版社,2005.
[21] Cheng-Yuan Chang, Kuo-Hung Chiang. Fuzzy projection control law and its applicationto the overhead crane[J]. Mechatronics,2008,18(10):607–615.
[22] Yang N, Fu Q, Wang S L, et al. Improvement of wavelet neural networks model andapplication[J]. Systems Engineering-Theory&Practice,2009,29(1):168-173.
[23] John R. Huey, Khalid L. Sorensen and William E. Singhose. Useful applications ofclosed-loop signal shaping controllers[J]. Control Engineering Practice,2008,(16)7:836–846.
[24] Diantong Liu, Jianqiang Yi and Dongbin Zhao. Adaptive sliding mode fuzzy control fora two-dimensional overhead crane[J]. Mechatronics,2005,(15)5:505–522.
[25]张文辉,齐乃明,伊洪亮.基于滑模变结构的空间机器人神经网络跟踪控制[J].控制理论与应用,2011,28(9):1141-1144.
[26] Cheng-Yuan Chang, Kuo-Hung Chiang. Fuzzy projection control law and its applicationto the overhead crane[J]. Mechatronics,2008,(18)10:607–615.
[27]张瑞军.闭环时滞滤波器消除二阶振荡系统残留振动的仿真研究[J].振动与冲击,2007,(26)11:163-164.
[28] Hong, K.-T.,&Hong, K.-S. Input shaping and VSC of container cranes[C]//IEEEInternational conference on control application, Taipei, Taiwan,2004:1570–1575.
[29] Huey, J.R., Sorensen, K.L.,&Singhose, W.E.. Useful applications of closed-loop signalshaping controllers[J], Control Engineering Practice,2008,(16)7,836–846.
[30] Matthew O.T. Cole. A discrete-time approach to impulse-based adaptive input shapingfor motion control without residual vibration[J]. Automatica,2011,(47)11:2504–2510.
[31] Cheng-Yuan Ch., Kou-Cheng Hsu and Kuo-Hung Chiang, An enhanced adaptive slidingmode fuzzy control for positioning and anti-swing control of the overhead cranesystem[C]//IEEE International Conference on Systems, Man and Cybernetics, Taipei,Taiwan, October,2006:992-997.
[32] Chen Zhimei, Zhang Jinggang and Zhaozhicheng, et. al, A new method of fuzzytime-varying sliding mode control[C]//Proceedings of the First International Conferenceon Machine Learning and Cybernetics. Beijing,2002:1789-1792.
[33] Cheng-Yuan Chang and Kuo-Hung Chiang, Fuzzy projection control law and itsapplication to the overhead crane[J]. Mechatronics,2008,(18):607-615.
[34] William Singhose, Lisa Porter and Michael Kenison, Effects of hoisting on the inputshaping control of gantry cranes[J]. Control Engineering Practice,2000,(8)10:1159-1165.
[35]董明晓,郑康平,姜虹.回转起重机载荷摆动模型及误差分析[J].系统仿真学报,2004,16(7):1398-1400.
[36]薛定宇,赵春娜,潘峰.基于框图的分数阶非线性系统仿真方法及应用[J].系统仿真学报,2006,18(9):2405-2408.
[37]曾庆山,曹广益,王振滨.分数阶PID控制器的仿真研究[J].系统仿真学报,2004,16(3):465-469.
[38] Vinagre B M, Podlubny I,Hernandez A, et. al.Some approximations of fractional orderoperators used in control theory and applications [J]. Fractional Calculus and AppliedAnalysis,2000,3(3):231-248.
[39]王乃州.基于分数阶微积分理论的滑模变结构控制[D].南京:南京林业大学,2010.
[40]孙宁,张华光,王智良.基于分数阶滑模面控制的分数阶超混沌系统的投影同步[J].物理学报,2011,60(5):111-117.
[41] Mehmet Onder. Fracional order sliding mode control with reaching law approach[J].Turk J Elec Eng&Comp Sci,2010,18(5):731-747.
[42]刘金坤.智能控制[M].电子工业出版社.2005.
[43] Optimization of tower crane and material supply locations in a high-rise building site bymixed-integer linear programming[J]. Automation in Construction,2011(20):571-580.
[44] J. Javadi-Moghaddam, A. Bagheri, An adaptive neuro-fuzzy sliding mode based geneticalgorithm control system for under water remotely operated vehicle[J]. Expert Systemswith Applications,2010(37):647-660.
[45]刘磊.基于遗传神经网络的指数跟踪优化方法[J].系统工程理论与实践,2010,30(1):22-29
[46] P.C. Chena, C.W. Chen, W.L. Chiang, GA-based modified adaptive fuzzy sliding modecontroller for nonlinear systems[J]. Expert Systems with Applications.2009,(36)3:5872-5879.
[47]王伟,易建强,赵冬斌,等.基于滑模方法的桥式吊车系统的抗摆控制[J].控制与决策,200419(9):1013-1016.
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[50]李彬.塔式起重机防摆控制与建模的微分几何方法[D].沈阳:东北大学,2005.
[51] Yang N, Fu Q, Wang S L, et al. Improvement of wavelet neural networks model andapplication[J]. Systems Engineering-Theory&Practice,2009,29(1):168-173.
[52]丁瑞华.基于神经网络算法的桥式起重机防摇摆控制[J].机电工程,2009(10):27-30.
[53]蔡自兴.智能控制原理与应用[M].清华大学出版社.2007.
[2] Hanafy M.Onla. Control of Gantry and Tower Cranes[D]. Blacksburg, Virginia,Virginia Polytechnic Institute and State University,January,2003.
[3] Parker, G., Groom, K., Hurtado, J. E., Feddema, J., Robinett, R.,&Leban, F.Experimental verification of a command shaping boom crane control system[C]//InAmerican control conference,1999,(1):86-90.
[4] Al-mousa A.A., Nayfeh A.H., Kachroo P.. Control of rotary cranes using fuzzylogic[C]//Proceedings of18th Biennial Conference on Mechanical Vibration and Noise,DET Pittsburgh, PA, September2001:2535-2544.
[5] Omar H.M., Nayfeh A.H.. A simple adaptive feedback controller for towercranes[C]//Proceedings of18th Biennial Conference on Mechanical Vibration andNoise, Pittsburgh, PA, September2001:2611-2621.
[6] S.Chatterjee. Vibration control by recursive time-delayed acceleration feedback[J].Journal of Sound and Vibration,2008,(317):67-70.
[7] Kunihiko Nakazono. Vibration control of load for rotary crane system using neuralnetwork with GA-based training[J]. Artif Life Robotics,2008,(13):98-101.
[8] Jorg Neupert, Eckhard Arnold and Klaus Schneider, Tracking and anti-sway control forboom cranes[J]. Control Engineering Practice,2010,(18)1:31–44.
[9] David Blackburn, Jason Lawrence. Radial-motion assisted command shapers fornonlinear tower crane rotational slewing[J]. Control Engineering Practice,2010,(18):523-531.
[10]李伟.基于动态误差最小的起重机最优消摆控制[J].电气自动化,2002,5:8-12.
[11]李伟,吴志新,齐保良.塔式起重机载荷摆动模型[J].机械工程学报,1993,29(4):15-22.
[12]齐伯文等.塔式起重机智能控制系统的最优反馈控制[J].哈尔滨建筑工程学报,1995,28(1):90-94.
[13]董明晓,张素,宋传增.回转起重机的建模与控制[J].机电产品开发与创新,2005,18(1):106-108.
[14]王建南,刘德君.基于模糊自适应PID控制的吊车防摆定位系统[J].微计算机信息,2007,23(22):35-80.
[15]张晓华，贾智勇.基于输入整形策略的船上回转吊车防摆控制[J].控制工程,2008,15(3):245-249.
[16]林贵瑜，杨新顺等.塔式起重栅吊装物摆动的控制[J].建筑机械化,2006,(11):34-36.
[17]刘晓胜.塔机运行的关键控制算法研究[J].科学技术与工程,2010,10(2):1671-1815.
[18] Zhen Z M, Meng W J, Zhang J G, et al. Scheme of sliding mode control based onmodified particle swarm optimization[J]. Systems Engineering-Theory&Practice,2009,29(5):137-141
[19] Michael Basin, Dario Calderon-Alvarez. Sliding mode regulator as solution to optimalcontrol problem for non-linear polynomial systems[J]. Journal of the Franklin Institute.2010(347):910–922.
[20]刘金坤.滑模变结构控制MATLAB仿真[M].北京:清华大学出版社,2005.
[21] Cheng-Yuan Chang, Kuo-Hung Chiang. Fuzzy projection control law and its applicationto the overhead crane[J]. Mechatronics,2008,18(10):607–615.
[22] Yang N, Fu Q, Wang S L, et al. Improvement of wavelet neural networks model andapplication[J]. Systems Engineering-Theory&Practice,2009,29(1):168-173.
[23] John R. Huey, Khalid L. Sorensen and William E. Singhose. Useful applications ofclosed-loop signal shaping controllers[J]. Control Engineering Practice,2008,(16)7:836–846.
[24] Diantong Liu, Jianqiang Yi and Dongbin Zhao. Adaptive sliding mode fuzzy control fora two-dimensional overhead crane[J]. Mechatronics,2005,(15)5:505–522.
[25]张文辉,齐乃明,伊洪亮.基于滑模变结构的空间机器人神经网络跟踪控制[J].控制理论与应用,2011,28(9):1141-1144.
[26] Cheng-Yuan Chang, Kuo-Hung Chiang. Fuzzy projection control law and its applicationto the overhead crane[J]. Mechatronics,2008,(18)10:607–615.
[27]张瑞军.闭环时滞滤波器消除二阶振荡系统残留振动的仿真研究[J].振动与冲击,2007,(26)11:163-164.
[28] Hong, K.-T.,&Hong, K.-S. Input shaping and VSC of container cranes[C]//IEEEInternational conference on control application, Taipei, Taiwan,2004:1570–1575.
[29] Huey, J.R., Sorensen, K.L.,&Singhose, W.E.. Useful applications of closed-loop signalshaping controllers[J], Control Engineering Practice,2008,(16)7,836–846.
[30] Matthew O.T. Cole. A discrete-time approach to impulse-based adaptive input shapingfor motion control without residual vibration[J]. Automatica,2011,(47)11:2504–2510.
[31] Cheng-Yuan Ch., Kou-Cheng Hsu and Kuo-Hung Chiang, An enhanced adaptive slidingmode fuzzy control for positioning and anti-swing control of the overhead cranesystem[C]//IEEE International Conference on Systems, Man and Cybernetics, Taipei,Taiwan, October,2006:992-997.
[32] Chen Zhimei, Zhang Jinggang and Zhaozhicheng, et. al, A new method of fuzzytime-varying sliding mode control[C]//Proceedings of the First International Conferenceon Machine Learning and Cybernetics. Beijing,2002:1789-1792.
[33] Cheng-Yuan Chang and Kuo-Hung Chiang, Fuzzy projection control law and itsapplication to the overhead crane[J]. Mechatronics,2008,(18):607-615.
[34] William Singhose, Lisa Porter and Michael Kenison, Effects of hoisting on the inputshaping control of gantry cranes[J]. Control Engineering Practice,2000,(8)10:1159-1165.
[35]董明晓,郑康平,姜虹.回转起重机载荷摆动模型及误差分析[J].系统仿真学报,2004,16(7):1398-1400.
[36]薛定宇,赵春娜,潘峰.基于框图的分数阶非线性系统仿真方法及应用[J].系统仿真学报,2006,18(9):2405-2408.
[37]曾庆山,曹广益,王振滨.分数阶PID控制器的仿真研究[J].系统仿真学报,2004,16(3):465-469.
[38] Vinagre B M, Podlubny I,Hernandez A, et. al.Some approximations of fractional orderoperators used in control theory and applications [J]. Fractional Calculus and AppliedAnalysis,2000,3(3):231-248.
[39]王乃州.基于分数阶微积分理论的滑模变结构控制[D].南京:南京林业大学,2010.
[40]孙宁,张华光,王智良.基于分数阶滑模面控制的分数阶超混沌系统的投影同步[J].物理学报,2011,60(5):111-117.
[41] Mehmet Onder. Fracional order sliding mode control with reaching law approach[J].Turk J Elec Eng&Comp Sci,2010,18(5):731-747.
[42]刘金坤.智能控制[M].电子工业出版社.2005.
[43] Optimization of tower crane and material supply locations in a high-rise building site bymixed-integer linear programming[J]. Automation in Construction,2011(20):571-580.
[44] J. Javadi-Moghaddam, A. Bagheri, An adaptive neuro-fuzzy sliding mode based geneticalgorithm control system for under water remotely operated vehicle[J]. Expert Systemswith Applications,2010(37):647-660.
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