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Titlebook: Bounded Dynamic Stochastic Systems; Modelling and Contro Hong Wang Book 2000 Springer-Verlag London 2000 Control Engineering.Control Theory

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发表于 2025-3-21 18:35:17 | 显示全部楼层 |阅读模式
期刊全称Bounded Dynamic Stochastic Systems
期刊简称Modelling and Contro
影响因子2023Hong Wang
视频video
发行地址Broaches new ground in considering a wide range of system output distributions.Fault detection methods applicable in diverse control situations..
学科分类Advances in Industrial Control
图书封面Titlebook: Bounded Dynamic Stochastic Systems; Modelling and Contro Hong Wang Book 2000 Springer-Verlag London 2000 Control Engineering.Control Theory
影响因子Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system. such as minimum variance control and mean value control. The general assumption used in the formulation of modelling and control strategies is that the distribution of the random signals involved is Gaussian. In this book, a set of new approaches for the control of the output probability density function of stochastic dynamic systems (those subjected to any bounded random inputs), has been developed. In this context, the purpose of control system design becomes the selection of a control signal that makes the shape of the system outputs p.d.f. as close as possible to a given distribution. The book contains material on the subjects of: - Control of single-input single-output and multiple-input multiple-output stochastic systems; - Stable adaptive control of stochastic distributions; - Model reference adaptive control; - Control of nonlinear dynamic stochastic systems; - Condition monitoring of bounded stochastic distr
Pindex Book 2000
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Control of Mimo Stochastic Systems: Robustness and Stability,derived. However, in practice many systems are subjected to multiple inputs and external disturbances. An added modelling error will also present when B-spline functions are used to approximate the output probability density function of the stochastic system. As such, a control algorithm for MIMO st
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Model Reference Adaptive Control,formulate the algorithm. In this chapter, an alternative approach will be described using the state space model. We will only consider unknown continuous-time linear systems, where the model reference adaptive control algorithm ([20, 21, 19, 25]) will be applied to design stable adaptive control inp
发表于 2025-3-22 19:51:30 | 显示全部楼层
Control of Nonlinear Stochastic Systems, to work well for some linear systems ([41, 44]). However, due to the wide existence of nonlinear systems in practice, it is also important to investigate the control algorithms for the control of the output probability density functions for general nonlinear stochastic systems. This forms the main
发表于 2025-3-23 00:34:43 | 显示全部楼层
Application to Fault Detection,seeking effective solutions to an improved reliability of practical control systems. As a result, many methods have been developed in the past two decades. In general, these approaches can be classified into the following three groups:
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Advanced Topics,been made on the control of the total shape of the output probability density functions of stochastic systems. In these approaches, the stochastic system considered has its outputs taken as the measured probability density functions of the system output and its inputs as a set of deterministic varia
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