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| 基于BP网络的飞轮电池电力转换控制研究 | |
| 引用本文： | 蒋宇,汤双清,李志雄,刘侃.基于BP网络的飞轮电池电力转换控制研究[J].控制工程,2010,17(2). |
| 作者姓名： | 蒋宇 汤双清 李志雄 刘侃 |
| 作者单位： | 1. 黄山学院,信息工程学院,安徽,黄山,245013 2. 三峡大学,机械与材料学院,湖北,宜昌,443002 3. 湖南大学,电气工程学院,湖南,长沙,410082 |
| 基金项目： | Supported by Educational Department of Hubei Province Natural Science Program(2033A001);;Hubei Province Natural Science Foundation(2005ABA294) |
| 摘 要： | 飞轮电池储能用集成电机时变非线性特点使得传统PID控制难以得到理想的控制性能,为此基于BP神经网络研究了一种新颖的飞轮电池电力转换器。该控制器结合BP神经网络自学习能力和PID控制的全局渐近稳定性能,通过神经网络在线优化调节PID参数,以实现对飞轮电池的高性能控制。其中,采用变学习速率的神经网络学习算法,学习速率随收敛过程误差的大小而自适应地进行调整,同时使用遗传算法(GA)优化得到PID参数的初始值,这可加快神经网络学习训练的收敛速度并避免陷入局部最小,进一步提高控制性能;另外,PWM采用SVPWM技术以增强能量转换效率和减小转矩脉动。数字仿真表明,基于所提出的BP-PID控制的电力转换矢量控制系统能够使飞轮电池在充放电两端都具有较快动态响应,较小超调,较高稳态精度以及较强的鲁棒性,控制效果明显比传统PID好。 |
| 关 键 词： | 飞轮电池 BP神经网络 PID 遗传算法 |
On Flywheel Battery Power Conversion Control Based on BP Neural Network |
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| JIANG Yu,TANG Shuang-qing,LI Zhi-xiong,LIU Kan.On Flywheel Battery Power Conversion Control Based on BP Neural Network[J].Control Engineering of China,2010,17(2). | |
| Authors: | JIANG Yu TANG Shuang-qing LI Zhi-xiong LIU Kan |
| Affiliation: | 1.College of Information Engineering/a>;China Huangshan University/a>;Huangshan 245013/a>;China/a>;2.College of Mechanical and Material Eng/a>;Three Gorges University/a>;Yichang 443002/a>;3.College of Electrical & Electronics Engineering/a>;Hunan University/a>;410082/a>;China |
| Abstract: | An adaptive PID BP neural network(NN)controller is developed for flywheel battery power conversion.The self-study ability of the BP NN and the global asymptotic stability of PID control are integrated,by which the high performance control is realizable in flywheel battery control through online optimizing the PID gains by using the BP NN.The variable learning rate strategy is applied,by which the learning speed is adaptive adjusted according to the convergence error.The genetic algorithm is employed to opti... |
| Keywords: | flywheel battery BP neural network proportional-integral-derivative controller GA |
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