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首页> 外文期刊>European Journal of Control >Temporal stabilizability and compensatability of time-varying linear discrete-time systems with white stochastic parameters
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Temporal stabilizability and compensatability of time-varying linear discrete-time systems with white stochastic parameters

机译:带有白色随机参数的时变线性离散时间系统的时间稳定性和可补偿性

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This paper reveals that apart from changes of system structure vital system properties such as stabilizability and compensatability may be lost temporarily due to the stochastic nature of system parameters. To that end new system properties called temporal mean-square stabilizability (tms-stabilizability) and temporal mean-square compensatability (tms-compensatability) for time-varying linear discrete-time systems with white stochastic parameters (multiplicative white noise) are developed. When controlling such systems by means of (optimal) state feedback, tms-stabilizability identifies intervals where mean-square stability (ms-stability) is lost temporarily. This is vital knowledge to both control engineers and system scientists. Similarly, tms-compensatability identifies intervals where ms-stability is lost temporarily in case of full-order (optimal) output feedback. Tests explicit in the system matrices are provided to determine each temporal system property. These tests compute measures of the associated temporal system properties. Relations among the new system properties as well as relations with associated existing system properties are investigated and established. Examples illustrating principal applications and practical importance are provided. (C) 2015 European Control Association. Published by Elsevier Ltd. All rights reserved.
机译:本文揭示,除了系统结构的变化外,由于系统参数的随机性,重要的系统属性(如稳定性和可补偿性)可能会暂时丢失。为此,针对具有白色随机参数(乘性白噪声)的时变线性离散时间系统,开发了称为时间均方稳定度(tms稳定度)和时间均方可补偿性(tms可补偿性)的新系统属性。当通过(最佳)状态反馈来控制此类系统时,tms稳定度可确定间隔,其中均方根稳定度(ms稳定性)会暂时丢失。这对于控制工程师和系统科学家都是至关重要的知识。类似地,tms可补偿性可识别在全阶(最佳)输出反馈的情况下暂时失去ms稳定性的时间间隔。提供在系统矩阵中显式的测试以确定每个时间系统属性。这些测试计算相关的临时系统属性的度量。研究并建立了新系统属性之间的关系以及与之关联的现有系统属性的关系。提供了说明主要应用和实际重要性的示例。 (C)2015欧洲控制协会。由Elsevier Ltd.出版。保留所有权利。

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