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首页> 外文期刊>IEEE Transactions on Automatic Control >A Fully Probabilistic Design for Tracking Control for Stochastic Systems With Input Delay
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A Fully Probabilistic Design for Tracking Control for Stochastic Systems With Input Delay

机译：输入延迟随机系统跟踪控制的完全概率设计

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This article studies model reference adaptive control (MRAC) for a class of stochastic discrete time control systems with time delays in the control input. In particular, a unified fully probabilistic control framework is established to develop the solution to the MRAC, where the controller is the minimizer of the Kullback-Leibler divergence between the actual and desired joint probability density functions of the tracking error and the controller. The developed framework is quite general, where all the components within this framework, including the controller and system tracking error, are modeled using probabilistic models. The general solution for arbitrary probabilistic models of the framework components is first obtained and then demonstrated on a class of linear Gaussian systems with time delay in the main control input, thus obtaining the desired results. The contribution of this article is twofold. First, we develop a fully probabilistic design framework for MRAC, referred to as model reference fully probabilistic design, for stochastic dynamical systems. Second, we establish a systematic pedagogic procedure that is based on deriving explicit forms for the required predictive distributions for obtaining the causal form of the randomized controller when input delays are present.
机译：本文研究了一类随机离散时间控制系统的模型参考自适应控制（MRAC），控制输入中的时间延迟。特别地，建立一个统一的完全概率控制框架以将解决方案开发给MRAC，其中控制器是跟踪误差和控制器的实际和期望的关节概率密度函数之间的kullback-leibler发散的最小化器。开发的框架非常一般，在此框架内的所有组件，包括控制器和系统跟踪错误，使用概率模型建模。首先获得框架组件的任意概率模型的一般解决方案，然后在主控制输入中的一类线性高斯系统上进行说明，从而获得所需的结果。这篇文章的贡献是双重的。首先，我们为MRAC开发了一个完全概率的设计框架，称为模型参考全概率设计，用于随机动力系统。其次，我们建立一个系统的教学程序，该过程基于用于在存在输入延迟时获取随机控制器的因果形式的所需预测分布的明确表格。

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