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Minimum entropy control for non-linear and non-Gaussian two-input and two-output dynamic stochastic systems

机译:非线性和非高斯两输入两输出动态随机系统的最小熵控制

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摘要

In this study, the problem of control algorithm design for a class of nonlinear two-input and two-output systems with non-Gaussian disturbances is investigated, where a general non-linear auto-regressive moving average with exogenous model is used to describe the system. Based on the deduced probability density functions of tracking errors, a new performance index is established using the entropy and joint entropy so as to characterise the uncertainty of the tracking errors of the closed-loop system. This performance also includes the expectations of tracking errors and the constrains of control energy. A recursive optimisation control algorithm is obtained by minimising the performance index. Moreover, the local stability condition of the closed-loop systems is established after some formulations. Finally, the comparative simulation results are presented to show that the performance of the proposed algorithm is superior to that of proportional-integral-derivative controller.
机译:本研究研究了一类具有非高斯扰动的非线性两输入两输出系统的控制算法设计问题,其中使用带有外生模型的一般非线性自回归移动平均值来描述系统。基于推导的跟踪误差概率密度函数,利用熵和联合熵建立了一个新的性能指标,以表征闭环系统跟踪误差的不确定性。此性能还包括对跟踪错误的期望以及对控制能量的约束。通过最小化性能指标来获得递归优化控制算法。此外,通过一些公式确定了闭环系统的局部稳定性条件。最后,通过比较仿真结果表明,所提算法的性能优于比例积分微分控制器。

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  • 来源
    《Control Theory & Applications, IET》 |2012年第15期|p.2434-2441|共8页
  • 作者

    Zhang J.; Ren M.; Wang H.;

  • 作者单位

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, People's Republic of China;

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  • 正文语种 eng
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