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APPLICATION OF MODEL REDUCTION FOR MODEL PREDICTIVE control

IFAC Proceedings Volumes 2002年第1期35卷 393-398页

作者： Juergen Hahn Uwe Kruger Thomas F. Edgar Department of Chemical Engineering University of Texas at Austin Austin TX 78712-1062 U.S.A. Lehrstuhl für Prozesstechnik RWTH Aachen D - 52056 Aachen Germany Intelligent Systems & Control Group Queen's University of Belfast Belfast BT9 5AH United Kingdom

In this paper model reduction methods are used to obtain a nonlinear process model for designing a model predictive controller (MPC). The corresponding controller and its closed-loop response is then compared with controllers that are determined from the original model and a linearized version of this model. The reduced dimensional nonlinear MPC controller performs almost as well as the nonlinear MPC controller that is based on the original model and considerably better than the linear MPC controller.

关键词： Model-based control Model reduction Nonlinear systems controllability Observability System analysis

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control relevant identification with steady state gain matching 6

Control relevant identification with steady state gain match...

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6th European control Conference, ECC 2001

作者： Shreesha, C. Gudi, Ravindra D. Interdisciplinary Program in Systems and Control Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India Department of Chemical Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

ISBN: (纸本)9783952417362

The prefilter based control relevant identification scheme proposed by Rivera et al.[14], for single input single output(SISO) system gives a model of the system which matches the true system in a range of frequencies that are important for closed loop performance. However, it may also be desirable to have small mismatch at the steady state condition as well. This is specifically true when the desired closed loop speed of response is much higher than the open loop speed of response. Here a method is proposed to estimate a control relevant model that, in addition to having a small mismatch in the control relevant frequencies, also has a good steady state gain match, with that of the true system. With such a control relevant model having steady state gain match, the closed loop internal model control (IMC) based system is shown to give satisfactory response even with higher desired speed of response. Also, a control relevant identification scheme for multi input single output(MISO) system, having steady state gain match is proposed, using uncorrelated inputs. Application of these identified models to a feed forward control scheme has been considered to demonstrate superior performance with these models. Similarly, with combined feed forward/feedback control, the model having steady state gain match gives an improved performance even with higher desired speed of closed loop response. © 2001 EUCA.

关键词： Linear systems

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Integrated identification and model predictive control using iterative refinement

Integrated identification and model predictive control using...

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2001 American control Conference

作者： Yang, L. Rivera, D.E. Control Systems Engineering Lab. Dept. of Chemical and Materials Eng. Arizona State University Tempe AZ 85287-6006 United States

An iterative refinement approach is presented for designing a high performance control system for an imprecisely known plant. The design procedure involves the integration of identification and model predictive control (MPC) using repeated closed-loop identification tests and successively improving the model (and ultimately, closed-loop performance) with each successive iteration. The method is appealing to industrial practice because real-time closed-loop data can be used directly to enhance the performance of a predictive controller without the need to deactivate the control loop during identification testing. The iterative refinement strategy is "plant-friendly" in that it tries to keep the identification test as short as possible while keeping the plant within operating limits and constraint. Constraint enforcement (on controlled, associated and manipulated variables) is naturally implemented through the use of MPC. The application of the method is demonstrated on a highly nonlinear diabatic (i.e., non-adiabatic) continuous stirred tank reactor problem.

关键词： Integrated control

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Integrated identification and model predictive control using iterative refinement

Integrated identification and model predictive control using...

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American control Conference (ACC)

作者： Lei Yang D.E. Rivera Control Systems Engineering Laboratory Department of Chemical and Materials Engineering Arizona State University Tempe AZ USA

An iterative refinement approach is presented for designing a high performance control system for an imprecisely known plant. The design procedure involves the integration of identification and model predictive control (MPC) using repeated closed-loop identification tests and successively improving the model (and ultimately, closed-loop performance) with each successive iteration. The method is appealing to industrial practice because real-time closed-loop data can be used directly to enhance the performance of a predictive controller without the need to deactivate the control loop during identification testing. The iterative refinement strategy is "plant-friendly" in that it tries to keep the identification test as short as possible while keeping the plant within operating limits and contraints. Constraint enforcement (on controlled, associated and manipulated variables) is naturally implemented through the use of MPC. The application of the method is demonstrated on a highly nonlinear diabatic (i.e., nonadiabatic) continuous stirred tank reactor problem.

关键词： Predictive models Predictive control control systems Testing Open loop systems Iterative methods Refining control design Nonlinear control systems Continuous-stirred tank reactor

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Time varying weighting generalized predictive control (TGPC): an application to a 1.5 MW free turbine engine

Time varying weighting generalized predictive control (TGPC)...

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IEEE Conference on control Technology and Applications (CCTA)

作者： H.W. Gomma D.H. Owens D. Rossiter Electronics and Communications Department Helwan University Helwan Egypt Department of Automatic Control and systems Engineering University of Sheffield UK Department of Chemical Engineering Loughborough University Loughborough UK

This paper describes the control design of a 1.5 MW free turbine with complex load. A nonlinear model of the engine with load has been developed within Simulink from details previously presented by Hill (1987). New predictive control technique, the so-called time varying weighting generalized predictive control (TGPC) is performed using a linearised model to represent the key components in the control design. The performance criteria are specified in terms of the stability margins, bandwidth and desired response of the engine to a severe load disturbance. The substantial change in system dynamics and the constraints on its manipulated variable (i.e. the throttle valve angle) offer a challenge to control engineers. Therefore, nonlinear simulations with parameter changes and full robustness/stability analysis are presented to support the conclusion that the design is robust/stable.

关键词： Predictive control control design Engines Robust stability Turbines Load modeling Predictive models Stability criteria Bandwidth Manipulator dynamics

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A data driven subspace approach to predictive controller design

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IFAC Proceedings Volumes 2001年第25期34卷 365-370页

作者： Ramesh Kadali Biao Huang Anthony Rossiter Department of Chemical and Materials Engineering University of Alberta Edmonton AB T6G 2G6 Canada Department of Automatic Control and Systems Engineering Sheffield University Mappin Street Sheffield Sl SJD UK

This paper is concerned with the design of predictive control without using the traditional dynamic model such as the state-space, input-output transfer function or step response model. The predictor or Kalman filter is obtained directly from the input/output experiment data. Certain matrices required by the predictor are calculated by decomposing data into past and future sections as used in the subspace identification method. Subspace approach eliminates the intermediate step of model structure selection such as model order and time-delay determination or truncation of the step response model in the identification stage, which simplifies the design procedure of the predictive controllers. However, subspace approach in its original form does not possess all important traditional predictive control features such as inclusion of an integrator for offset-free control, constraint handling, feedforward option and tuning of controllers through the disturbance model. These are several problems, among others, to be addressed in this paper. The proposed predictive controller is demonstrated on a pilot scale system.

关键词： Model predictive control subspace identification feedforward control constraint handling noise model

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MISO structure based control-relevant identification of MIMO systems

MISO structure based control-relevant identification of MIMO...

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American control Conference (ACC)

作者： C. Shreesha R.D. Gudi N.M.A.M. Institute of Technology Udupi Karnataka India Interdisciplinary Program in Systems and Control Engineering Indian Institute of Technology Mumbai India Department of Chemical Engineering Indian Institute of Technology Mumbai India

The prefilter based open loop control-relevant identification scheme proposed for single input single output (SISO) systems by D.E. Rivera et al. (1992) is extended for multi input multi output (MIMO) systems using a multi input single output (MISO) structural framework. By selecting input output pair for control, the MIMO system is partitioned into individual SISO systems with the interacting branches acting on each SISO loop being treated as structured measured disturbances (in addition to the regular disturbance at each output). With this consideration, a methodology is proposed for design of separate prefilters for the individual channels, taking into account the performance specifications for each loop. The use of an uncorrelated set of inputs is proposed for obtaining accurate estimation of individual channel elements. The prefiltering for each individual loop has been shown to give good estimates of the control-relevant model for the direct as well as the interacting branches. Closed loop simulations, using decoupled internal model controllers, involving representative processes taken from the literature demonstrate the validity of the approach.

关键词： control systems MIMO Open loop systems Frequency response control design control engineering chemical engineering chemical technology Process control control system synthesis

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A model Reduction Method for Monitoring Large-scale Processes

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IFAC Proceedings Volumes 2001年第22期34卷 425-430页

作者： Uwe Kruger Xun Wang S. Joe Qin Intelligent Systems and Control Group Queens University of Belfast BT9 5AH. U.K Department of Mechanical Engineering. The University of Manchester. M13 9PL U.K. Department of Chemical Engineering The University of Texas at Austin. TX 78712 U.S.A

In this paper, a novel identification method, termed as latent variable least squares (LVLS) is introduced. LVLS describes linear steady-state process behavior by a reduced dimensional model. This is particularly useful for large-scale processes, which often present a considerable number of highly correlated process variables. Additionally, it is shown that LVLS can be utilized for process monitoring. In an application study on a real industrial process, it is shown that LVLS performs better than partial least squares, which is a competitive method that is similar in approach.

关键词： Model Reduction Industrial Production systems Statistical Process control Large-Scale systems Fault Detection

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Design of Minimum Crest Factor Multisinusoidal Signals for "Plant-Friendly" Identification of Nonlinear Process systems

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IFAC Proceedings Volumes 2000年第15期33卷 1097-1102页

作者： M.W. Braun R. Ortiz-Mojica D.E. Rivera Department of Chemical Bio and Materials Engineering Control Systems Engineering Laboratory Manufacturing Institute Arizona State University Tempe Arizona USA 85287-6006

Guidelines for specifying design parameters for minimum crest factor multisine signals per the approach of Guillaume et al. are presented. These guidelines are evaluated for the identification of nonlinear process systems. The minimum crest factor multisine signals offer some distinct advantages over both Schroeder phased multisine signals and m-level Pseudo-Random Sequence (m-level PRS) signals with respect to "plant-friendliness" considerations. These signals can be used to reduce the effects of nonlinearity in obtaining an empirical transfer function estimate (ETFE). As an example, the ETFE of a Rapid Thermal Processing (RTP) reactor simulation is constructed. "Plant-friendly" issues are also discussed and illustrated in the identification and control of a CSTR simulation via "Model-on-Demand" estimation. This provides a compelling example, since the "Model-on-Demand" estimator is a data-driven nonlinear identification approach.

关键词： nonlinear model identification local modeling nonlinear model predictive control multisine signals input signal design

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Beyond Step Testing and Process Reaction Curves: Introducing Meaningful System Identification Concepts in the Undergraduate chemical engineering Curriculum

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IFAC Proceedings Volumes 2000年第15期33卷 815-820页

作者： D.E. Rivera M.E. Flores Department of Chemical Bio and Materials Engineering and Control Systems Engineering Laboratory Manufacturing Institute Arizona State University Tempe Arizona 85287-6006 phone:(480)-965-9476

This paper describes efforts at Arizona State University to introduce substantive topics in system identification to undergraduate chemical engineering students. Specifically, the paper focuses on how system identification issues relevant to industrial practice have been incorporated into a simulated gas-oil furnace experiment that is part of a senior-level process dynamics and control course (ChE 461).

关键词： education identification chemical process control

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