• 计算机应用研究 , 2013,Vol.30(12)
  • 基于QCNN的非线性跟踪问题研究
  • 牛德智    陈长兴    符 辉    赵延明    屈 坤    王旭婧   
  • 空军工程大学 理学院, 西安 710051
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摘要:

针对如何快速准确地跟踪到非线性系统的状态问题, 研究了量子细胞神经网络(QCNN)在非线性跟踪中的应用。在满足Lyapunov函数指数收敛的条件下, 设计了一种新型参数形式的控制器, 在此基础上, 对三种非线性系统即确定性非线性运动、参数和运动规律未知的非线性数据系统以及典型蔡氏电路进行了QCNN跟踪研究。仿真结果表明, 在QCNN系统中, 通过设计合理的控制器可以实现非线性问题状态的有效跟踪, 且实验结果为QCNN系统复杂度与跟踪的及时性之间关系提供了参考依据和有力的说明。设计的新型控制器及对实际问题处理方法为QCNN的理论及应用研究具有借鉴意义。

关键词: 非线性跟踪   蔡氏电路   量子细胞神经网络   Lyapunov函数   控制器  

基金:

陕西省电子信息综合集成重点实验室项目(201107Y16); 军内武器系统科研项目(KJ2010182, KJ2012184)

 

 

Research for nonlinear tracking problem based on QCNN

NIU De-zhi   CHEN Chang-xing   FU Hui   ZHAO Yan-ming   QU Kun   WANG Xu-jing  

  

Abstract:

Aiming at method of tracking status of nonlinear system quickly and timely, this paper studied application of QCNN in nonlinear tracking system. In the case that Lyapunov function was convergent in exponent rate, it designed one controller with other parameter. On the basis of this controller, QCNN controlled system tracked three kinds of nonlinear system, which were separately certain system, nonlinear data system without known parameters and its function relation, and system of Chua's circuit. Simulations show that QCNN system can realize effective tracking for status of nonlinear problem by suitable controller. Furthermore, the simulation results provide reference and illustration to relationship between system's complexity and accurate exhausted time of tracking. The new designed controller and disposing adopted methods in the paper can give some thinking means for QCNN theory and its application research.

Keywords: nonlinear tracking   QCNN (quantum cellular neural networks)   Lyapunov function   controller   Chua's circuit