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首页> 外文期刊>IEEE Transactions on Control Systems Technology >Synchronization of Underactuated Unknown Heavy Symmetric Chaotic Gyroscopes via Optimal Gaussian Radial Basis Adaptive Variable Structure Control
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Synchronization of Underactuated Unknown Heavy Symmetric Chaotic Gyroscopes via Optimal Gaussian Radial Basis Adaptive Variable Structure Control

机译:最优高斯径向基自适应变结构控制的欠驱动未知重对称混沌陀螺仪同步

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摘要

This brief proposes modified projective synchronization (MPS) methods for underactuated unknown heavy symmetric chaotic gyroscope systems via optimal Gaussian radial basis adaptive variable structure control. Chaotic gyroscope systems are considered as underactuated systems where a control input is designed to synchronize the two degree of freedoms interactions. Until now, no investigation of this subject with one control input has been presented. The importance of obtaining synchronization objectives is specified when the dynamics of gyroscope system are unknown. In this brief, using the neural variable structure control technique, a control law is established that guarantees the MPS of underactuated unknown chaotic gyros. In the neural variable structure control, Gaussian radial basis functions are utilized to estimate online the system dynamic functions. Adaptation laws of the online estimator are derived in the sense of the Lyapunov function. Moreover, online and offline optimizers are applied to optimize the energy of the control signal. The proposed solution is generalized to chaos control of the mentioned gyroscopes. Numerical simulations are presented to verify the proposed synchronization methods.
机译:本文通过优化的高斯径向基自适应变结构控制,为欠驱动的未知重对称混沌陀螺仪系统提出了改进的投影同步(MPS)方法。混沌陀螺仪系统被认为是欠驱动系统,其控制输入被设计为同步两个自由度相互作用。到现在为止,还没有提出通过一个控制输入对该对象进行调查。当陀螺仪系统的动力学未知时,说明获得同步目标的重要性。在本文中,使用神经变量结构控制技术,建立了控制律,该控制律可确保欠驱动的未知混沌陀螺仪的MPS。在神经变结构控制中,利用高斯径向基函数在线估计系统动态函数。在线估计器的适应律是从Lyapunov函数的意义上得出的。此外,应用在线和离线优化器来优化控制信号的能量。所提出的解决方案被普遍用于提到的陀螺仪的混沌控制。数值模拟被提出来验证所提出的同步方法。

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