基于MQRBVSC的重对称混沌未知陀螺仪同步与混沌控制

2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI) Pub Date : 2016-10-01 DOI:10.1109/ICICPI.2016.7859664

P. Deori, A. B. Kandali

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引用次数: 1

摘要

针对欠驱动陀螺仪(主从)系统参数已知和未知的情况，提出了一种利用多重二次径向基函数神经网络(MQRBFNN)辨识器实现系统混沌同步的变结构控制方法。陀螺仪是非线性欠驱动系统，具有混沌运动。混沌控制是在系统参数已知的情况下，利用VSC的Lyapunov稳定性判据设计恒定、指数和功率趋近律三个控制律来实现的。对于未知的系统参数，MQRBFNN标识符被训练用于在线估计器。研究结果表明，在系统参数已知的情况下，VSC利用功率趋近规律，实现了较好的同步效果。采用功率趋近律的MQRBFNN辨识器可在系统参数未知的情况下实现较好的同步。

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Synchronization and chaos control of heavy symmetric chaotic unknown gyroscope using MQRBVSC

In this paper a new method of Variable Structure Control (VSC) using Multiquadric Radial Basis Function Neural Network (MQRBFNN) identifier is proposed to achieve chaos synchronization of underactuated gyroscope (master-slave) system with known and unknown system parameters. Gyroscopes are nonlinear underactuated systems which show chaotic motions. Chaos control is achieved by designing three control laws (constant, exponential and power rate reaching law) using Lyapunov stability criteria using VSC under known system parameters. For unknown system parameters, MQRBFNN identifiers are trained for online estimators. In this work it is shown that VSC using power rate reaching law, achieves better synchronization under known system parameters. It is also found that with MQRBFNN identifier based VSC using power rate reaching law, good synchronization is achieved under unknown system parameters.

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2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI)

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