| 塔式起重机的神经网络滑模防摆控制 |
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| 引用本文： | 孙辉,陈志梅,孟文俊.塔式起重机的神经网络滑模防摆控制[J].系统工程理论与实践,2013,33(10):2708-2713. |
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| 作者姓名： | 孙辉 陈志梅 孟文俊 |
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| 作者单位： | 1. 太原科技大学 电子信息工程学院, 太原 030024;2. 太原科技大学 机械工程学院, 太原 030024 |
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| 基金项目： | 国家自然科学基金(51075289); 山西省自然科学基金(2011011011-2); 太原科技大学博士启动基金(20122014); 太原科技大学研究生科技创新项目(20111007) |
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| 摘 要： | 针对塔式起重机存在的负载摆动, 分析塔式起重机的动力学模型, 提出了一种基于遗传算法的塔式起重机神经网络滑模防摆控制新方法. 利用RBF神经网络输出逼近系统的不确定项, 并运用遗传算法优化滑模控制器的参数, 使得参数的收敛速度加快. 该方法削弱了滑模控制系统的高频抖振, 提高了系统的控制性能, 改善了系统的控制品质. 仿真结果表明方法的有效性和可行性.
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| 关 键 词： | 塔式起重机 滑模控制 神经网络 遗传算法 |
| 收稿时间： | 2011-07-11 |
Neural network sliding mode anti-swing control for tower crane |
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| SUN Hui,CHEN Zhi-mei,MENG Wen-jun.Neural network sliding mode anti-swing control for tower crane[J].Systems Engineering —Theory & Practice,2013,33(10):2708-2713. |
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| Authors: | SUN Hui CHEN Zhi-mei MENG Wen-jun |
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| Institution: | 1. School of Electronics and Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;2. School of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China |
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| Abstract: | Aiming to the swing of load in the process of transportation, the dynamic model of tower crane system is analyzed. Based on genetic algorithm, a new method of neural network sliding mode anti-swing control is proposed for tower crane. The outputs of neural networks are used to approach the uncertainties of the positioning subsystem and the anti-swing subsystem. The parameters of the controller are optimized with genetic algorithm (GA), which can improve the convergence speed of parameters. This method weakens the system chattering which sliding mode control (SMC) bring out, enables the system to have good dynamic performances and enhance the quality of control system. The simulation results show that the feasibility and effectiveness of the method. |
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| Keywords: | tower crane sliding mode control neural network genetic algorithm |
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