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混沌动力系统的混合内模控制与比例控制

Hybrid internal model control and proportional control of chaotic dynamical systems.

作者信息

Qi Dong-lian, Yao Liang-bin

机构信息

College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China.

出版信息

J Zhejiang Univ Sci. 2004 Jan;5(1):62-7. doi: 10.1007/BF02839314.

Abstract

A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

摘要

提出了一种利用混沌或避免混沌的新混沌控制方法。引入了混合内模控制和比例控制学习方案。为了获得期望的鲁棒性能并确保系统的稳定性,还开发了自适应动量算法。通过合理设计神经网络对象模型和神经网络控制器,在修改BP神经网络参数的同时对混沌动力学系统进行控制。以洛伦兹混沌系统为例,结果表明该控制策略可将混沌动力学系统稳定在期望轨道上。

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