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closed-loop identification of MIMO systems: An excitation-free approach

COMPUTERS & CHEMICAL ENGINEERING 2025年 194卷

作者： Zhang, Zhi-Qiang Huang, Chun-Qing Xiamen Univ Dept Automat Xiamen 361005 Peoples R China

In general, the external excitation is indispensable for closed-loop identification of SISO and MIMO systems. In this paper, an excitation-free approach for closed-loop identification of multi-delay MIMO systems is proposed by using the routine operating closed-loop data. Both identifiability and consistency of the plant model estimation are achieved when the basic assumptions are met. The proposed approach provides an effective way to handle closed-loop identification of MIMO systems, while it becomes of a non-trivial task for the conventional identification methods and especially subspace identification method in lack of prior knowledge on the process. The effectiveness of the proposed approach is demonstrated by a 4 x 4 industrial example viz. the Alatiqi column.

关键词： Mimo systems closed-loop identification Excitation-free Routine operating data

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closed-loop identification with routine operating data: Effect of time delay and sampling time

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JOURNAL OF PROCESS CONTROL 2011年第7期21卷 997-1010页

作者： Shardt, Yuri A. W. Huang, Biao Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 2V4 Canada

In industry, in order to store the reams of data that are collected from all the different flow, level, and temperature sensors, the fast-sampled data is very often downsampled before being stored in a data historian. This downsampled or even compressed data is, then, often used by process engineers to recover the appropriate process parameters. However, little has been written about the effects of the sampling on the quality of the model obtained. Therefore, in this paper, the effects of sampling time are investigated from both a theoretical and practical perspective using results that come out of the theory of closed-loop system identification with routine operating data. It is shown that if the discrete time delay in a process is sufficiently large or the sampling time is sufficiently small, then it is possible to recover the true system parameters. The most common industrial processes that fulfill this constraint are temperature control loops. These results suggest that the sampling time has an important bearing on the quality of the model estimated from routine operating data. Using both Monte Carlo simulations and an experimental set-up with a heated tank, the effect of discrete time delay on the identification of the true continuous time parameters was considered for different sampling times. It was shown that increasing the sampling time above a given threshold resulted in identifying an incorrect model. As well, the models obtained using a PID controller were less sensitive to sampling time than those obtained using a PI controller. However, the PID controller values were more sensitive to the effects of aliasing at larger sampling times. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： closed-loop identification Routine operating data closed-loop identifiability

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closed-loop identification and model predictive control of extractive dividing-wall column

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CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION 2019年 142卷 107552-000页

作者： Feng, Zemin Shen, Weifeng Rangaiah, G. P. Dong, Lichun Chongqing Univ Sch Chem & Chem Engn Chongqing 400044 Peoples R China Natl Univ Singapore Dept Chem & Biomol Engn Singapore 117585 Singapore Chongqing Univ Natl Municipal Joint Engn Lab Chem Proc Intensifi Chongqing 400044 Peoples R China Chongqing Univ Minist Educ Key Lab Lowgrade Energy Utilizat Technol & Syst Chongqing 400044 Peoples R China

Extractive dividing-wall column (EDWC) is a promising thermally-coupled system for separating multiple azeotrope or close-boiling mixtures;however, its intensified structure with relatively small physical space and strong interactions makes model predictive control (MPC) an attractive scheme for EDWC operation. The performance of MPC strongly depends on the accuracy of the dynamic model. The presence of recycled entrainer stream in EDWC makes it impossible to identify the dynamic model of EDWC using open-loop experiments. In the present study, a proportional-integral (PI) control strategy based on temperature difference was first studied for EDWC operation. Subsequently, a systematic closed-loop identification experiment was implemented to identify a dynamic model, and an MPC was designed using the identified model. The results indicate that the accuracy of the identified model is sufficient to design MPC controller for EDWC operation. Both direct and indirect manipulation of vapor split ratio were considered in MPC. The transient responses of product purities indicate that MPC is better than PI for EDWC operation for rejecting disturbances in feed flow rate and composition, even though MPC shows slow dynamic responses compared to PI control for rejecting feed composition disturbances.

关键词： Model predictive control Extractive distillation Extractive dividing-wall column Temperature difference control closed-loop identification Proportional-integral control

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closed-loop identification via output fast sampling

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JOURNAL OF PROCESS CONTROL 2004年第5期14卷 555-570页

作者： Wang, JD Chen, TW Huang, B Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 2G6 Canada

This paper addresses a challenge: Is a closed-loop system without external excitation identifiable? The so-called fast-sampling direct approach provides a positive answer. It removes a traditional restrictive identifiability condition for linear output feedback closed-loop systems, i.e., an external persistently exciting test signal is not required. Identifiability is analyzed using the lifting technique, the bifrequency map and bispectrum concepts. The proposed approach is further investigated and evaluated by simulation. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： closed-loop identification fast-sampling direct approach cyclo-stationarity bifrequency maps bispectra

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closed-loop identification of MIMO systems in the Prediction Error framework: Data informativity analysis

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AUTOMATICA 2020年 121卷 109171-109171页

作者： Colin, Kevin Bombois, Xavier Bako, Laurent Morelli, Federico Univ Lyon UMR CNRS 5005 Ecole Cent Lyon Lab Ampere Ecully France Ctr Natl Rech Sci CNRS Paris France

In the Prediction Error identification framework, it is essential that the experiment yields informative data with respect to the chosen model structure to get a consistent estimate. In this work, we focus on the data informativity property for the identification of multi-inputs multi-outputs systems in closed-loop and we derive conditions to verify if a given external excitation combined with the feedback introduced by the controller yields informative data with respect to the chosen model structure. This study covers the case of multiple-inputs multiple-outputs model structures that are natural generalizations of the classical single-input single-output model structures used in Prediction Error identification and the classical types of external excitation vectors, i.e., vectors whose elements are either multisine or filtered white noises. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： System identification closed-loop identification MIMO systems Prediction Error methods Consistency

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closed-loop identification of plant and disturbance models based on data-driven generalized minimum variance regulatory control

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JOURNAL OF PROCESS CONTROL 2022年 115卷 197-208页

作者： Uematsu, Ryota Masuda, Shiro Kano, Manabu Tokyo Metropolitan Univ Grad Sch Syst Design Dept Mech Syst Engn 6-6 Asahigaoka Hino Tokyo Japan Kyoto Univ Dept Syst Sci Kyoto Japan

The paper addresses a closed-loop identification method based on generalized minimum variance (GMV) evaluation. Since the proposed method uses routine operation data, it requires no extra experiment with an external excitation signal. The model parameters of the plant and the disturbance are obtained simultaneously using a single set of input-output data generated by stochastic disturbance. A new variance criterion for closed-loop identification is derived through the conversion of the GMV evaluation function that has originally been developed for data-driven regulatory control. In the conversion, the feedback invariant polynomial, which is estimated from time series analysis of the closed-output signal, plays a key role. The features of the proposed approach lead to bridge closed loop identification with control performance assessment as well as data-driven controller parameters tuning. The paper proves that the optimization of the proposed criterion results in the unique optimal solution, which corresponds to the true plant and disturbance model parameters. In numerical examples, the proposed method is applied to datasets obtained from a continuous stirred tank reactor (CSTR), which is operated around an unstable steady state. The result illustrates the effectiveness of the proposed closed-loop identification method.(C) 2022 Elsevier Ltd. All rights reserved.

关键词： closed-loop identification Generalized minimum variance Data-driven controller design

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closed-loop identification: a two step approach

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JOURNAL OF PROCESS CONTROL 1997年第6期7卷 425-438页

作者： Huang, B Shah, SL UNIV ALBERTA DEPT CHEM ENGN EDMONTON AB T6G 2G6 CANADA

The accuracy aspects of identification (with respect to both variance and bias of estimates) and the role of filtering in closed-loop identification is discussed in this paper. It is shown that the key difference between closed-loop and open-loop identification is the existence of the sensitivity function. A closed-loop identification algorithm which asymptotically yields the same expressions as open-loop identification, in both variance and bias errors, is proposed. The proposed algorithm is evaluated by simulated examples as well as experiments performed on a computer-interfaced pilot-scale process. (C) 1997 Elsevier Science Ltd.

关键词： closed-loop identification process identification prediction error methods reduced-complexity models

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closed-loop identification with a quantizer

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JOURNAL OF PROCESS CONTROL 2005年第6期15卷 729-740页

作者： Wang, M Thornhill, NF Huang, B UCL Dept Elect & Elect Engn London WC1E 7JE England Univ London Imperial Coll Sci Technol & Med Ctr Process Syst Engn London SW7 2BY England Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 2G6 Canada

This paper proposes a new closed-loop identification scheme for a single-input single-output (SISO) control loop based upon a quantizer inserted into the feedback path. The quantizer can be used to generate an equivalent persistently exciting signal to which the well known two-stage method of closed-loop identification can be applied. The paper examines the performance and behaviour of the quantizer-based closed-loop identification and gives suggestions for the choice of quantizer interval. Simulation and experimental examples are used to illustrate the proposed new CLID scheme. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： chemical process closed-loop identification frequency response quantization persistently exciting PID control power spectrum process control process monitoring

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closed-loop identification revisited

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AUTOMATICA 1999年第7期35卷 1215-1241页

作者： Forssell, U Ljung, L Linkoping Univ Dept Elect Engn Div Automat Control S-58183 Linkoping Sweden

identification of systems operating in closed loop has long been of prime interest in industrial applications. The problem offers many possibilities, and also some fallacies, and a wide variety of approaches have been suggested, many quite recently. The purpose of the current contribution is to place most of these approaches in a coherent framework, thereby showing their connections and display similarities and differences in the asymptotic properties of the resulting estimates. The common framework is created by the basic prediction error method, and it is shown that most of the common methods correspond to different parameterizations of the dynamics and noise models. The so-called indirect methods, e.g., are indeed "direct" methods employing noise models that contain the regulator. The asymptotic properties of the estimates then follow from the general theory and take different forms as they are translated to the particular parameterizations. We also study a new projection approach to closed-loop identification with the advantage of allowing approximation of the open-loop dynamics in a given, and user-chosen frequency domain norm, even in the case of an unknown, nonlinear regulator. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： system identification closed-loop identification prediction error methods modelling statistical analysis

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closed-loop identification with an unstable or nonminimum phase controller

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AUTOMATICA 2002年第12期38卷 2127-2137页

作者： Codrons, B Anderson, BDO Gevers, M Univ Catholique Louvain CESAME B-1348 Louvain Belgium Laborelec SC Prod Line Proc Control B-1630 Linkebeek Belgium Australian Natl Univ Res Sch Informat Sci & Engn Canberra ACT 0200 Australia

In many practical cases, the identification of a system is done in closed loop with some controller. In this paper, we show that the internal stability of the resulting model, in closed loop with the same controller, is not always guaranteed if this controller is unstable and/or nonminimum phase, and that the classical closed-loop prediction-error identification methods present different properties regarding this stability issue. With some of these methods, closed-loop instability of the identified model is actually guaranteed. This is a serious drawback if this model is to be used for the design of a new controller. We give guidelines to avoid the emergence of this instability problem;these guidelines concern both the experiment design and the choice of the identification method. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： closed-loop identification internal stability ustable or nonminimurn phase controller control design

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