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Design of a nuclear reactor controller using a model predictive control method

KSME INTERNATIONAL JOURNAL 2004年第12期18卷 2080-2094页

作者： Na, MG Jung, DW Shin, SH Lee, SM Lee, YJ Jang, JW Lee, KB Chosun Univ Dept Nucl Engn Kwangju 501759 South Korea Cheju Natl Univ Dept Nucl & Energy Engn Jeju Do 690756 South Korea Korea Atom Energy Res Inst Taejon 305600 South Korea

A model predictive controller is designed to control thermal power in a nuclear reactor. The basic concept of the model predictive control is to solve an optimization problem for finite future time steps at current time, to implement only the first optimal control input among the solved control inputs, and to repeat the procedure at each subsequent instant. A controller design model used for designing the model predictive controller is estimated every time step by applying a recursive parameter estimation algorithm. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), was used to verify the proposed controller for a nuclear reactor. It was known that the nuclear power controlled by the proposed controller well tracks the desired power level and the desired axial power distribution.

关键词： nuclear reactor control model predictive control load-following operation nuclear power level control axial shape index (ASI) control recursive parameter estimation

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SEQUENTIAL estimation OF THE parameterS OF REGRESSION MODEL

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CYBERNETICS AND SYSTEMS ANALYSIS 2005年第4期41卷 631-634页

作者： Stepashko, V. S. Efimenko, S. N. Natl Acad Sci Ukraine Int Sci & Training Ctr Informat Technol & Syst Kiev Ukraine Minist Educ & Sci Ukraine Kiev Ukraine

Modified Gauss and Gram-Schmidt methods are proposed for recursive estimation of the parameters of sequentially complicated structures of regression models in observation-based simulation. Run times of these algorithm... 详细信息

关键词： observation-based simulation recursive parameter estimation embedded structures bordering method

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Real-Time Identification of LCL Filters Employed With Grid Converters

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2020年第5期56卷 5158-5169页

作者： Pirsto, Ville Kukkola, Jarno Rahman, F. M. Mahafugur Hinkkanen, Marko Aalto Univ Dept Elect Engn & Automat Espoo 02150 Finland

This article presents a real-time identification method for LCL filters used with three-phase grid converters. The method can be applied to identify both the inductance and capacitance values of the filter and the series resistance seen by the converter. As a side-product, an estimate of the grid inductance seen from the point of connection is also obtained. A wideband excitation signal is added to the converter voltage reference. During the excitation, converter current and converter voltage reference samples are used for identification. The samples are preprocessed in real time by removing dc biases and significant grid-frequency harmonics. parameters of two discrete-time models are estimated at each sampling instant with a recursive estimation algorithm. Depending on the estimated model, the model parameter estimates are translated to either the resistance or the inductance and capacitance values of the system. The method can be embedded to a control system of pulsewidth-modulation-based converters in a plug-in manner. Only the dc-link voltage and converter currents need to be measured. Simulation and experimental results are presented for a 12.5-kVA grid converter system to evaluate the proposed method.

关键词： Grid converter LCL filter real-time identification recursive parameter estimation

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Real-time Identification Method for LCL Filters Used With Grid Converters 11

Real-time Identification Method for LCL Filters Used With Gr...

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11th Annual IEEE Energy Conversion Congress and Exposition (ECCE)

作者： Pirsto, Ville Kukkola, Jarno Rahman, F. M. Mahafugur Hinkkanen, Marko Aalto Univ Sch Elect Engn Espoo Finland

ISBN: (纸本)9781728103952

This paper presents a real-time algorithm for identifying the inductance and capacitance values of LCL filters used with grid converters. As a side product, the grid inductance seen from the point of common coupling is also estimated. A wideband excitation signal is added to the converter voltage reference. During the excitation, the converter currents and the converter voltage reference are sampled. The samples are preprocessed in real time by removing DC biases and significant grid-frequency harmonics. parameters of a discrete-time model are estimated at each sampling instant with a recursive estimation algorithm. The model parameter estimates are translated into inductance and capacitance values. The method can be embedded to a control system of PWM-based converters in a plug-in manner. Only the DC-link voltage and converter currents need to be measured. Simulation and experimental results are presented for a 12.5kVA grid converter system to evaluate the proposed method.

关键词： Grid converter LCL filter real-time identification recursive parameter estimation

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Real-Time Identification of LCL Filters Employed With Grid Converters

Real-Time Identification of LCL Filters Employed With Grid C...

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11th Annual IEEE Energy Conversion Congress and Exposition (ECCE)

作者： Pirsto, Ville Kukkola, Jarno Rahman, F. M. Mahafugur Hinkkanen, Marko Aalto Univ Dept Elect Engn & Automat Espoo 02150 Finland

关键词： Grid converter LCL filter real-time identification recursive parameter estimation

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An Adaptive Dual MPC Scheme based on Output Error Models parameterized using Generalized Orthonormal Basis Filters

An Adaptive Dual MPC Scheme based on Output Error Models Par...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Kumar, Kunal Patwardhan, Sachin C. Noronha, Santosh Indian Inst Technol Syst & Control Engn Bombay Maharashtra India Indian Inst Technol Dept Chem Engn Bombay Maharashtra India

A significant fraction of industrial MPC schemes employ linear prediction models. Closed loop performance of a linear model based MPC scheme can deteriorate over a period of time if the prediction model is not updated to account for the changing operating conditions. A possible remedy to this problem is on-line update of the model parameters under the closed loop conditions. An effective way of handling this problem is through dual control, which directs the plant output towards a reference setpoint and simultaneously injects probing signals into the plant to get information-rich data. In this work, an adaptive dual MPC scheme is developed for controlling MIMO systems based on output error models (OE) parameterized using generalized orthogonal basis filters (GOBF). A nominal model is initially developed using offline identification exercise. The Fourier coefficients of GOBF-OE models are then updated online using recursive least squares algorithm. Similar to Kumar et al. [2015], the MPC formulation is modified to include terms that are sensitive to the parameter covariance and are capable of injecting probing perturbations into the system as and when required. A distinguishing feature of the proposed work is the use of state space realizations of GOBF networks for model development and prediction. Simulation studies using the benchmark quadruple tank system (Johansson [2000]) reveal that the proposed approach provides sufficient degrees of freedom to excite the plant in closed loop for generating information rich data for model parameter estimation. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Dual control MPC Adaptive Control Predictive Control Orthogonal Basis Filters recursive parameter estimation

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Nonlinear control of a wastewater pH neutralisation process using adaptive NARX models

Nonlinear control of a wastewater pH neutralisation process ...

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1996 IEEE International Conference on Systems, Man and Cybernetics - Information, Intelligence and Systems

作者： Hong, T Morris, AJ Karim, MN Zhang, J Luo, W Univ of Newcastle Newcastle upon Tyne United Kingdom

ISBN: (纸本)7800033813

This paper describes a comprehensive approach to the control of a wastewater pH neutralisation process which consists of a linear dynamic part with a long time delay and a severely nonlinear static part with an extremely high gain. Varying buffer capacity is also a characteristic of the process. Nonlinear predictive control (NPC) schemes are used based on adaptive nonlinear autoregressive with exogenous inputs (NARX) models. The initial structure and parameters are identified off-line with a modified orthogonal forward regression (MOFR) algorithm. In order to avoid estimator windup due to poor excitation of on line data, the modified least squares incorporating exponential resetting and forgetting algorithm (EFRA) and setpoint perturbation are applied to adaptively adjust the parameters of a NARX model. Several aspects of NPC are discussed. Comparisons of nonadaptive control, adaptive control without and with setpoint perturbation, and adaptive control with the noisy measurement are carried out to demonstrate the performance of the proposed schemes.

关键词： predictive control pH neutralisation recursive parameter estimation NARX models

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FlexNet Wide Area Monitoring System

FlexNet Wide Area Monitoring System

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Terzija, V. Regulski, P. Kunjumuhammed, L. P. Pal, B. C. Burt, G. Abdulhadi, I. Babnik, T. Osborne, M. Hung, W. Univ Manchester Sch Elect & Elect Engn Manchester Lancs England

ISBN: (纸本)9781457710018

This paper presents the results of collaborative research from the SUPERGEN FlexNet Consortium into Wide Area Monitoring, Protection and Control (WAMPAC). The focus of the research addresses the design and development of an optimal WAMPAC architecture, communication infrastructure and real-time WAMPAC applications which will play an important role in future GB power network operation and understanding. The article concludes with an assessment of inter-area oscillations based on data records captured by the wide area monitoring system (WAMS) established as part of the FlexNet project.

关键词： Wide Area Monitoring Protection and Control synchrophasors inter-area oscillations recursive parameter estimation

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An Adaptive Dual MPC Scheme based on Output Error Models parameterized using Generalized Orthonormal Basis Filters

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IFAC-PapersOnLine 2017年第1期50卷 9077-9082页

作者： Kumar K. Patwardhan S.C. Noronha S. Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai India

A significant fraction of industrial MPC schemes employ linear prediction models. Closed loop performance of a linear model based MPC scheme can deteriorate over a period of time if the prediction model is not updated to account for the changing operating conditions. A possible remedy to this problem is on-line update of the model parameters under the closed loop conditions. An effective way of handling this problem is through dual control, which directs the plant output towards a reference setpoint and simultaneously injects probing signals into the plant to get information-rich data. In this work, an adaptive dual MPC scheme is developed for controlling MIMO systems based on output error models (OE) parameterized using generalized orthogonal basis filters (GOBF). A nominal model is initially developed using o-ine identification exercise. The Fourier coe¢cients of GOBF-OE models are then updated online using recursive least squares algorithm. Similar to Kumar et al. [2015], the MPC formulation is modified to include terms that are sensitive to the parameter covariance and are capable of injecting probing perturbations into the system as and when required. A distinguishing feature of the proposed work is the use of state space realizations of GOBF networks for model development and prediction. Simulation studies using the benchmark quadruple tank system (Johansson [2000]) reveal that the proposed approach provides su¢cient degrees of freedom to excite the plant in closed loop for generating information rich data for model parameter estimation. © 2017

关键词： Adaptive Control Dual control MPC Orthogonal Basis Filters Predictive Control recursive parameter estimation

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A State Observer from Multilevel Quantized Outputs

A State Observer from Multilevel Quantized Outputs

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Argentine Conference on Automatic Control (AADECA)

作者： Carlos Gomez, Juan Sad, Gonzalo D. Univ Nacl Rosario CIFASIS CONICET Rosario Santa Fe Argentina Univ Nacl Rosario FCEIA Rosario Santa Fe Argentina

ISBN: (纸本)9789874685933

In this paper, a Kalman Filter type algorithm is introduced for the recursive estimation of the states of linear systems whose outputs are measured through sensors with multilevel quantized outputs. It is also shown how the algorithm can be adapted for the parameter estimation of linear systems in linear regression form, from quantized outputs. The influence of the quantization step on the performance of the proposed algorithms is analyzed through simulation examples.

关键词： Kalman Filter State Observer recursive parameter estimation Quantized Data

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