CAJ | 학술논문

提出了基于Chebyshev正交函数神经网络的不确定性混沌系统的鲁棒自适应同步方法.首先,本文提出了正交函数神经网络的网络结构,分析了利用Chebyshev正交多项式形成神经网络的机理.利用Lyapunov稳定性定理确定正交函数神经网络控制器的权值更新规则,并保证权值误差和跟踪误差的有界性.该方法能克服不确定性对混沌系统同步的破坏,实现了良好的同步效果.在本文最后,针对Lorenz系统进行了数值计算,数值计算结果表明了所给方法的有效性.
제출료기우Chebyshev정교함수신경망락적불학정성혼돈계통적로봉자괄응동보방법.수선,본문제출료정교함수신경망락적망락결구,분석료이용Chebyshev정교다항식형성신경망락적궤리.이용Lyapunov은정성정리학정정교함수신경망락공제기적권치경신규칙,병보증권치오차화근종오차적유계성.해방법능극복불학정성대혼돈계통동보적파배,실현료량호적동보효과.재본문최후,침대Lorenz계통진행료수치계산,수치계산결과표명료소급방법적유효성.
By using Chebyshev orthogonal neural network, we propose a robust adaptive synchronization method for a class of uncertain chaotic system. The structure of the orthogonal function neural network is first introduced, and then, the principle of orthogonal neural network is analyzed by using Chebyshev orthogonal polynomials. We derive the adaptive rule for the weights of neural network by using Lyapunov stability theorem, and ensure that both adapted weight errors and the tracking error are bounded. The simulation results show that the proposed approach can effectively eliminate the disruption of perturbation. Finally, a Lorenz system is employed to verify the effectiveness of the proposed method, and the simulation results are shown in the end of this paper.