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Control Strategies for Digital Twin Systems
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作者 Guo-Ping Liu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期170-180,共11页
With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies ... With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples. 展开更多
关键词 digital twin control systems fault tolerant control model tracking performance prediction performance retention
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Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information 被引量:10
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作者 Dong Shen Yun Xu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI 2016年第1期59-67,共9页
An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to gua... An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to guarantee an adaptive improvement in tracking performance. A decreasing learning gain is introduced into the algorithm to suppress the effects of stochastic noises and quantization errors. The input sequence is proved to converge strictly to the optimal input under the given index. Illustrative simulations are given to verify the theoretical analysis. © 2014 Chinese Association of Automation. 展开更多
关键词 ALGORITHMS digital control systems Discrete time control systems Iterative methods Learning algorithms Stochastic control systems Stochastic systems
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Transfer Function Model of Multirate Feedback Control Systems
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作者 肖建 唐磊 《Journal of Modern Transportation》 2001年第1期1-7,共7页
Based on the suitably defined multivariable version of Kranc operators and the extended input and output vectors, the multirate sampling plant is transformed to a equivalent time invariant single rate one, then the t... Based on the suitably defined multivariable version of Kranc operators and the extended input and output vectors, the multirate sampling plant is transformed to a equivalent time invariant single rate one, then the transfer function model of the multivariable multirate sampling plant is obtained. By combining this plant model with the time invariant description of the multirate controller in terms of extended vectors, the closed loop transfer function model of the multirate feedback control system can be determinated. This transfer function model has a very simple structure, and can be used as a basis for the analysis and synthesis of the multirate sampling feedback control systems in the frequency domain. 展开更多
关键词 feedback control transfer functions multirate digital control systems computer control
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