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Iterative design of structured uncertainty models and robust controllers based on closed-loop data

IET CONTROL THEORY AND APPLICATIONS 2010年第12期4卷 2823-2836页

作者： Roedoenyi, G. Gaspar, P. Hungarian Acad Sci Comp & Automat Res Inst Syst & Control Lab H-1111 Budapest Hungary

A joint uncertainty modelling and robust control design method is presented for linear time-invariant (LTI) systems. The system is given as a linear fractional transformation (LFT) with structured uncertainty blocks. The goal is to optimise the robust performance of the closed loop by simultaneously creating an optimised uncertainty model consistent with measurement data and designing a robust controller using skew mu synthesis. The proposed modelling/validation and control design algorithm is placed in the iterative identification and control (IIC) framework (design-experiments-analysis loop). In the proposed IIC approach, weighting functions of structured perturbation models are designed, which may lead to less conservative controllers compared to unstructured perturbations and disturbances. No a priori information is required on the disturbances. An advantage of the proposed method in the mu-synthesis context is that the number of fixed design parameters used in robust control (typically frequency-dependent weighting functions) is reduced to those associated with the control performance specification. The weighting functions of the uncertainty model are parameterised in the frequency domain and tuned subject to model validation constraints. It is shown that using skew mu as a robust performance criterion for both uncertainty modelling and control design, the proposed scheme simultaneously improves the robustness and performance of the control system. The efficiency of the method is illustrated on a vehicle steering problem.

关键词： structured perturbation models robust control design design-experiments-analysis loop iterative design robust controllers control system synthesis Stability in control theory joint uncertainty modelling linear time-invariant systems Control system analysis and synthesis methods structured uncertainty blocks closed loop systems linear systems linear fractional transformation structured uncertainty models identification uncertain systems vehicle steering problem closed-loop data iterative identification control frequency-dependent weighting functions

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Identification of reheat furnace temperature models from closed-loop data - an industrial case study

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ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING 2006年第1-2期1卷 70-81页

作者： Samyudia, Yudi Sibarani, Hatopan Curtin Univ Technol Sch Engn Sci Discipline Chem Engn Miri Sarawak 98100 Malaysia McMaster Univ Dept Chem Engn Hamilton ON L8S 4L8 Canada

This work deals with the application of prediction error (PE) method to identify the furnace temperature models from a set of closed-loop data. In this study, we gather a set of measurement data of the set points of the furnace zone temperatures as inputs and the furnace sidewall temperatures as outputs under a dynamic change of the slab pace rate. Owing to the complexity of its process dynamics, we assume no knowledge about the nature of the feedback mechanism. By treating the slab pace rate as an additive external signal, we show that the closed-loop data is informative for applying a direct approach to the closed-loop identification using the PE method, but only for a particular class of model structures. Model validation results support this analysis, in which the identified ARX, Box-Jenkins, and state-space models are reasonably better than the identified FIR models, according to the Akaike's index and the one-step-ahead prediction criteria. The residual analysis reveals that the identified ARX, Box-Jenkins, and state-space models do satisfy a 99% confidence region of its auto- and cross-correlation functions. Moreover, we find out that, for the collected data, there is no significant difference in the model predictive quality when applying the MISO and MIMO PE methods using the state-space model structure. (C) 2006 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： identification closed-loop data reheat furnace temperature models

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data-Driven Predictive Control Using closed-loop data: An Instrumental Variable Approach

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IEEE CONTROL SYSTEMS LETTERS 2023年 7卷 3639-3644页

作者： Wang, Yibo Qiu, Yiwen Sader, Malika Huang, Dexian Shang, Chao Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Carnegie Mellon Univ Dept Philosophy Pittsburgh PA 15213 USA Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Dept Automat Beijing 100084 Peoples R China

Current data-driven predictive control (DDPC) methods heavily rely on data collected in open-loop operation with elaborate design of inputs. However, due to safety or economic concerns, systems may have to be under feedback control, where only closed-loop data are available. In this context, it remains challenging to implement DDPC using closed-loop data. In this letter, we propose a new DDPC method using closed-loop data by means of instrumental variables (IVs). We point out that the original DDPC fails to represent all admissible trajectories due to feedback control. By drawing from closed-loop subspace identification, the use of two forms of IVs is suggested to address this issue and the correlation between inputs and noise. Furthermore, a new DDPC formulation with a novel IV-inspired regularizer is proposed, where a balance between control cost minimization and weighted least-squares data fitting can be made for improvement of control performance. Numerical examples and application to a simulated industrial furnace showcase the improved performance of the proposed DDPC based on closed-loop data.

关键词： Technological innovation Predictive control Instruments Feedback control Linear systems Costs Correlation data-driven predictive control instrumental variables closed-loop data

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closed-loop data-Oriented Design of a PID Controller

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IFAC Proceedings Volumes 2012年第23期45卷 284-289页

作者： Kayoko Hayashi Toru Yamamoto Dept. of System Cybernetics Graduate School of Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima 739-8524 Japan(e-mail: hayashi-kayoko@hiroshima-u.ac.jp) Div. of Electrical Systems and Mathematical Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima 739-8524 JAPAN(e-mail: yama@hiroshima-u.ac.jp)

PID controllers have been widely employed in industrial processes. However, it is important to determine PID gains because the control performance is influenced by the PID gains. The conventional schemes have computed PID gains based on system models. The mathematical model should accurately describe the system property, however, it is difficult to obtained the strict mathematical model. In order to get suitable system parameters, it is necessary that the operating data satisfy the richness condition for parameter estimation. Therefore, it is the new PID controller design scheme which does not need the to determine directly PID gains based on the operating data. In this paper, a new method is not required to description model is proposed. The proposed scheme can give a suitable set of PID gains based on the operating data. If the operating data of controlled object and the desired reference model are prepared, the desired control performance can be obtained. The effectiveness of the proposed scheme is evaluated by two numerical examples and application to an injection molding process.

关键词： PID controller closed-loop data Model-free Control Process Control

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Design and Experimental Evaluation of a Performance-Driven PID Controller

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JOURNAL OF ROBOTICS AND MECHATRONICS 2016年第5期28卷 616-624页

作者： Yamamoto, Toru Kinoshita, Takuya Ohnishi, Yoshihiro Shah, Sirish L. Hiroshima Univ Inste Engn 1-4-1 Kagamiyama Higashihiroshima Hiroshima 7398527 Japan Hiroshima Univ Grad Sch Engn 1-4-1 Kagamiyama Higashihiroshima Hiroshima 7398527 Japan Ehie Univ Fac Educ 3 Bunkyocho Matsuyama Ehime 7908577 Japan Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada

This study proposes a performance-driven control method that performs a "control performance assessment" and a "control system design" from a set of closed-loop data. The method assesses control performance based on the minimum variance control law from closed-loop data. It also calculates a control parameter that improves the control performance from the same closed-loop data by using the fictitious reference iterative tuning (FRIT) method. This method is characterized by not requiring any system model. The effectiveness of this method is verified through a numerical simulation and an application result to a temperature control unit.

关键词： control performance assessment performance-driven control process control PID control closed-loop data

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Development of control-oriented models for a building under regular heating, ventilation and air-conditioning operation-a comparative simulation study and an experimental validation

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2023年第1期42卷 83-104页

作者： Shamachurn, Heman Hassen, Sayed Z. Sayed Univ Mauritius Dept Elect & Elect Engn Reduit 80837 Mauritius Univ Mauritius Dept Elect & Elect Engn Reduit 80837 Mauritius

The development of models is a major barrier to the fast and widespread adoption of model predictive control for building HVAC systems. This paper proposes the subspace identification technique, refined through the prediction error method, to quickly obtain a model for the accurate indoor temperature prediction, even with little identification data, even in the presence of large unmeasured disturbances and noisy identification data, and even using data which was collected during the regular HVAC operation of a building. The identification issues associated with grey-box models were thoroughly investigated. In particular, the development of a grey-box model was found to be a complex, lengthy and computationally intensive process, even for a single-zone building, and the models were not physically meaningful. The proposed method was found to be much easier and faster, with a potential for direct practical application. Analysis on experimental data from an existing building provided promising results.

关键词： subspace identification regular HVAC operation open-loop data closed-loop data RC model experimental validation DesignBuilder

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data-driven method for a single-input multi-output dual-rate system

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2018年第12期13卷 1837-1838页

作者： Ito, Sho Sato, Takao Araki, Nozomu Konishi, Yasuo Univ Hyogo Grad Sch Engn 2167 Shosha Himeji Hyogo 6712280 Japan

We propose a new data-driven method for a single-input multi-output dual-rate system, in which the sampling interval of plant outputs is an integer multiple of the holding interval of a control input. In the proposed method, the dual-rate system is converted to a multi-input multi-output single-rate system, and controller parameters are optimized using one-shot closed-loop data. Furthermore, the ripple-free condition is clarified. Finally, the effectiveness of the proposed method is shown through a numerical example. (c) 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： data-driven method dual-rate closed-loop data lifting method single-input multi-output FRIT

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Design of a Smart Adaptive Control System Based on Control Performance Evaluation 53

Design of a Smart Adaptive Control System Based on Control P...

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SICE Annual Conference (SICE)

作者： Kinoshita, Takuya Kishimoto, Akihiro Yamamoto, Toru Hiroshima Univ Grad Sch Engn Dept Syst Cybernet Hiroshima Japan Hiroshima Univ Inst Engn Div Elect Syst & Math Engn Hiroshima Japan

ISBN: (纸本)9784907764456

PID controllers have been widely used in a many process systems because of simple control structure and clear physical meaning of PID parameters. Among the PID tuning schemes, the VRFT (Virtual Reference Feedback Tuning) and the FRIT (Fictitious Reference Iterative Tuning) which determine control parameters by using closed-loop data have received much attention in recent years. This paper studies how to accomplish "controller design" and "control performance assessment" concurrently based on the GMVC (Generalized Minimum Variance Control). According to this scheme, PID parameters are directly determined by using a set of operating data. The effectiveness of the proposed method is evaluated by a simulation example.

关键词： PID Control Generalized Minimum Variance Control closed-loop data Control Performance Assessment

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closed-loop identification of stabilized models using dual input-output parameterization

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EUROPEAN JOURNAL OF CONTROL 2024年 80卷

作者： Chen, Ran Srivastava, Amber Yin, Mingzhou Smith, Roy S. Ecole Polytech Fed Lausanne EPFL Urban Transport Syst Lab CH-1015 Lausanne Switzerland Indian Inst Technol Dept Mech Engn Delhi 110016 New Delhi India Swiss Fed Inst Technol Swiss Fed Inst Technol Automatic Control Lab CH-8092 Zurich Switzerland

This paper introduces a dual input-output parameterization (dual IOP) for the identification of linear time- invariant systems from closed-loop data. It draws inspiration from the recent input-output parameterization developed to synthesize a stabilizing controller. The controller is parameterized in terms of closed-loop transfer functions, from the external disturbances to the input and output of the system, constrained to lie in a given subspace. Analogously, the dual IOP method parameterizes the unknown plant with analogous closed-loop transfer functions, also referred to as dual parameters. In this case, these closed-loop transfer functions are constrained to lie in an affine subspace guaranteeing that the identified plant is stabilized by the known controller. Compared with existing closed-loop identification techniques guaranteeing closed-loop stability, such as the dual Youla parameterization, the dual IOP requires neither a doubly-coprime factorization of the controller nor a nominal plant that is stabilized by the controller. The dual IOP does not depend on the order and the state-space realization of the controller either, as in the dual system-level parameterization. Simulation shows that the dual IOP outperforms the existing benchmark methods.

关键词： System identification closed-loop data closed-loop parameterization Stabilized models

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