基于CARIMA模型的全局收敛的多变量随机自适应控制算法

A Globally Convergent Multivariable Stochastic Adaptive Control Algorithm Based on CARIMA

中文关键词  随机多变量系统  系统的关联矩阵  全局收敛性  负载干扰

英文关键词  stochastic multivariable systems  system interactor  global convergence  load disturbance

中文摘要

      本文针对多变量受控自回归积分滑动平均模型（CARIMA）提出了新的直接随机自适应控制算法。该算法不仅能鲁棒抑制任何定常负荷干扰而且应用于非最小相位系统仍具有全局收敛性。该算法不要求事先知道系统的关联矩阵只要求知道关联矩阵的整值参数。

英文摘要

      In this paper a novel stochastic direct adaptive control algorithm for multivariable linear systems described by a Controlled Autoregressive Integrating Moving Average (CARIMA) model is proposed. This scheme not only ensures the robust offset rejection for any constant load disturbance acting on the plant but also has globally convergent properties even for non-minimum systems. In particular, it requires only knowledge of the integer valued parameters of the system interactor matrix.