文件名称:pid
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- 上传时间:2012-11-16
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人工神经网络(Artificial Neural Network)是从生理角度对智能的模拟,具有极
高的学习能力和自适应能力,能够以任意精度逼近任意函数,完成对系统的仿真;
而遗传算法是对自然界生物进化过程的模拟,具有极强的全局寻优能力,这两种
算法都是当下研究较多的智能方法。将这两种方法与常规的 PID 控制相结合,
构成智能 PID 控制器,使其具有参数自整定、自适应的能力,以适应复杂环境
下的控制要求,这一思路对提高控制效果具有很好的现实意义。
-Artificial Neural Network (ANN) is an imitation of the intelligence by the point of physiological. It has a high capacity of learning and adaptive, can approximate any function to arbitrary accuracy, and complete the simulation of the system. The Genetic
algorithm is a simulation of natural biological evolution, which has a strong ability of
global optimization. These two algorithms are more intelligent method of current
research. The idea of combining these two methods with the conventional PID
controller to be a intelligent controller with the abilities of parameter auto-tuning and
adaptive for the requirements of the complex environment, has a high practical
significance of improving the control effect.
高的学习能力和自适应能力,能够以任意精度逼近任意函数,完成对系统的仿真;
而遗传算法是对自然界生物进化过程的模拟,具有极强的全局寻优能力,这两种
算法都是当下研究较多的智能方法。将这两种方法与常规的 PID 控制相结合,
构成智能 PID 控制器,使其具有参数自整定、自适应的能力,以适应复杂环境
下的控制要求,这一思路对提高控制效果具有很好的现实意义。
-Artificial Neural Network (ANN) is an imitation of the intelligence by the point of physiological. It has a high capacity of learning and adaptive, can approximate any function to arbitrary accuracy, and complete the simulation of the system. The Genetic
algorithm is a simulation of natural biological evolution, which has a strong ability of
global optimization. These two algorithms are more intelligent method of current
research. The idea of combining these two methods with the conventional PID
controller to be a intelligent controller with the abilities of parameter auto-tuning and
adaptive for the requirements of the complex environment, has a high practical
significance of improving the control effect.
相关搜索: 自整定 PID
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基于遗传算法优化的智能控制研究.kdh
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