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Obviously, there will be an unbalanced load on each mechanism due to the irregular shape of moulds and the inaccurate installing locations. The synchronous performance of multiple rotating arms, during a large-angle rotating process, directly influences the service life of blade moulds and the production quality of wind blades. For the turnover mechanism to enjoy high reliability, adaptability and control accuracy, a new control method using the distributed single neuron PID algorithm is proposed for a synchronous control of angular displacement of rotating arms. An improved LMS algorithm is used in the learning process, and the gain of the neuron output is adjusted automatically by the neuron based on the motion analysis results. Through rotating motion analysis with iterations, some basic parameters are determined, and a mechanical and hydraulic combined simulation model in AMESim is established, including a planar mechanical model. 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分布式神经元PID在不均衡系统同步控制中的应用
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乌建中;侯贤士;陈 吉
科技导报 | 研究论文 2009,27(0923): 53-56
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分布式神经元PID在不均衡系统同步控制中的应用
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乌建中;侯贤士;陈 吉
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通讯作者:
侯贤士
Application of Distributed Neuron PID in Synchronous Controlling of an Unbalanced System
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    Corresponding Author:
    HOU Xian Shi
出版时间: 2009-12-13
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大型风电叶片模具的合模或脱模,采用双缸铰接的液压翻转机构,其在大角度翻转过程中多转臂同步性能将直接影响翻转模具的寿命和叶片生产质量。针对该翻转设备可靠性、适应性和控制精度要求较高的特点,提出一种分布式的单神经元PID控制算法对机构转臂进行角位移同步控制,学习过程采用改进的LMS算法,并根据运动分析结果实现神经元输出增益的自动调整。建立AMESim机液混合模型,通过动态共享内存运行LabVIEW神经元子VI。联合仿真结果和实际应用均表明,该方法对非线性、时变的不均衡系统具有良好的控制精度。
分布式  /  单神经元PID  /  同步  /  不均衡  /  AMESim
The hydraulic turnover mechanism, using a dual cylinder hinge, is an advanced blade mould closing equipment of high technologies, mostly used for megawatt class wind blades above 40 meters, where more than three mechanisms are arranged along one blade mould at the same time. Obviously, there will be an unbalanced load on each mechanism due to the irregular shape of moulds and the inaccurate installing locations. The synchronous performance of multiple rotating arms, during a large-angle rotating process, directly influences the service life of blade moulds and the production quality of wind blades. For the turnover mechanism to enjoy high reliability, adaptability and control accuracy, a new control method using the distributed single neuron PID algorithm is proposed for a synchronous control of angular displacement of rotating arms. An improved LMS algorithm is used in the learning process, and the gain of the neuron output is adjusted automatically by the neuron based on the motion analysis results. Through rotating motion analysis with iterations, some basic parameters are determined, and a mechanical and hydraulic combined simulation model in AMESim is established, including a planar mechanical model. The LabVIEW subprogram of neuron PID could be run through dynamic shared memory simultaneously. Finally, the results of traditional PID and neuron PID are shown in the same plot. It is shown through simulation results as well as practical applications that this method enjoys a good control accuracy for nonlinear and time variant unbalanced systems.
Distributed  /  Single neuron PID  /  Synchronous  /  Unbalance  /  AMESim
乌建中;侯贤士;陈 吉. 分布式神经元PID在不均衡系统同步控制中的应用. 科技导报, 2009 , 27 (0923) : 53 -56 .
. Application of Distributed Neuron PID in Synchronous Controlling of an Unbalanced System[J]. Science & Technology Review, 2009 , 27 (0923) : 53 -56 .

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  • 接收时间:2009-09-21
  • 首发时间:2009-12-13
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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