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检索条件"任意字段=Symposium on Dynamics and Control of Process Systems"

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Discrete-time optimal control of electric hot water tank

Discrete-time optimal control of electric hot water tank

引用

11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Beeker, Nathanael Malisani, Paul Petit, Nicolas EDF Lab EnerBatAve Renardieres Ecuelles F-77818 Moret Sur Loing France CAS MINES ParisTech 60 Bd St Michel F-75272 Paris France

The paper exposes a discrete time model with three states to represent the dynamics of an Electric Hot Water Tank (EHWT). This models stands halfway between distributed parameters equations and totally lumped single integrators. It allows a faithful reproduction of observed behaviors, especially those induced by stratification. It is also instrumental in formulating optimal control problems aiming at maximizing performance under comfort, constraints. In particular, it is shown how to recast such problems as a Mixed-Integer Linear Program (MILP) so that the problem can be solved with off-the-shelf software packages. Numerical results are presented. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Integer programming Linear programming Energy Storage Energy control Complementarity problems Discrete-time systems Dynamic modelling Load regulation Optimal control

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dynamics of nonlinear chemical process with multiplicative stochastic noise

Dynamics of nonlinear chemical process with multiplicative s...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Baratti, Roberto Tronci, Stefania Schaum, Alexander Alvarez, Jesus Univ Cagliari Dept Ingn Meccan Chim & Mat Via Marengo 2 I-09123 Cagliari Italy Univ Kiel Chair Automat Control Kaiserstr 2 D-24143 Kiel Germany UAM Dept Ingn Proc & Hidraul Apdo 55534 Mexico City 09340 DF Mexico

Motivated by problems in process design, monitoring and control, the effect of multiplicative stochastic uncertainty injection on the behavior of nonlinear dynamical system is studied with Fokker Planck theor for two rather simple case examples selected to draw rigorous results with analytic formulae. The effect of noise multiplicativeness on the shape of the stationary state PDF and of the transient one along deterministic, probability diffusion, and escape time scales is characterized. The findings are corroborated and illustrated With numerical simulations. The results provide insight to assist the improvement of numerical Monte Carlo and polynomial chaos methods for stochastic multi-state multi-noise dynamical chemical processes underline by complex nonlinear behavior. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Stochastic system Parameters uncertainty Fokker-Planck equation

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State Estimation and Model Predictive control for the systems with Uniform Noise

State Estimation and Model Predictive Control for the System...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Pavelkova, Lenka Belda, Kvetoslav Inst Informat Theory & Automat CAS Pod Vodarenskou Vezi 4 Prague 18208 8 Czech Republic

This paper concerns the model predictive control applied to tie systems with bounded uncertainties. These systems are described by a state-space model with uniformly distributed states and outputs with unknown bounds of respective distributions. The model matrices are assumed to be known. The approximate estimation of states and noise bounds is based on the Bayesian approach. A state-space generalised predictive control is selected as a suitable target, model predictive control strategy. The proposed concept of the above mentioned estimation within generalised predictive control is illustrated by representative comparative simulation examples. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Predictive control bounded noise probabilistic models linear state-space models

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control of a Solar Furnace using MPC with Integral Action

Control of a Solar Furnace using MPC with Integral Action

引用

11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Costa, Bertinho A. Lemos, Joao M. Guillot, Emmanuel Univ Lisbon INRSC ID IST Rua Alves Redol 9 P-1000029 Lisbon Portugal CNRS PROMES 7 Rue Four Solaire F-66120 Font Romeu France

Solar furnaces are devices employed in high temperature material stress tests that use concentrated solar energy. This process has a nonlinear dynamics caused by a fourth power temperature term and by the nonlinear behavior of the shutter. Sun power variability due to weather conditions may affect the operation of a solar furnace if it is not compensated by adjusting the shutter aperture. The contribution of this paper is to explore and to evaluate the application of model predictive control with integral action to a nonlinear process. Off-line identification is employed to characterize the temperature dynamics. This methodology avoids the use of online adaptation mechanisms that may cause stability problems during temperature stress tests that may melt the material sample. The aim is to design a controller with a good performance, able to track the temperature cycling profile without overshooting to avoid melting the material sample. Active cooling is also explored to improve the temperature tracking during the decrease of the temperature profile. Experimental results obtained from the closed loop control of the plant are presented. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Solar Furnace Non-linear dynamics Off-line Identification Incremental Model Predictive control

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Fault detection for simulated valve faults in a high pressure leaching process

Fault detection for simulated valve faults in a high pressur...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Miskin, Jason Lindner, Brian Auret, Lidia Dorfling, Christie Bradshaw, Steven Univ Stellenbosch Dept Proc Engn Private Bag X1 ZA-7602 Matieland South Africa

A simulation of a high pressure leaching process in a base metals refinery (BMR) is used to simulate fault conditions for two types of valve faults. The faults were modelled using empirical models fitted to actual process data from Western Platinum Ltd. BMR. The effects of the faults on process performance were determined. Following this, principal component analysis (PCA) was used to determine whether these faults could be detected. It was found that both faults had a significant effect on control performance, and that PCA was able to detect both faults accurately. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Fault detection dynamic modelling abnormal events

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process Discovery of Operator Actions in Response to Univariate Alarms

Process Discovery of Operator Actions in Response to Univari...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Hu, Wenkai Al-Dabbagh, Ahmad W. Chen, Tongwen Shah, Sirish L. Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 1H9 Canada Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada

To capture the experience of skilled operators in response to alarm notifications, a systematic method of process discovery for operator actions in response to univariate alarms is proposed. The contributions of the paper are two rods. First, the transitions of alarm States are defined and formulated as a Petri net model. Second, the methods of process discovery through Alarm & Event logs are presented, where the logs are segmented and reorganized in a format suitable for processing by process discovery algorithms. Finally, the effectiveness and practicality of the proposed methods are illustrated using an industrial case study. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Alarm systems human-in-the-loop operator actions workflow models

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Design of a Data-Driven controller for a Spiral Heat Exchanger

Design of a Data-Driven Controller for a Spiral Heat Exchang...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Wakitani, Shin Deng, Mingcong Yamamoto, Toru Tokyo Univ Agr & Technol Koganei Tokyo 1848588 Japan Hiroshima Univ Hiroshima 7398527 Japan

A data proportional-integral-derivative (DD-PID) controller has been proposed as an effective controller for nonlinear systems. The DD-PID controller can tune the PID parameters adaptively at each equilibrium point. In order to train the PID parameters in a database, an offline learning algorithm based on a fictitious reference iterative tuning (FRIT) method was established. This method can compute the PID parameters by using a set of operating data. However, the FRIT method is a control parameter tuning method that is only based on the minimization of the system output in its criterion;therefore, the criterion is insufficient, for systems in which the stability of a closed-loop system is important, such as chemical process systems because sometimes the sensitivity of an obtained controller becomes high. In order to solve this problem, an extended FRIT (E-FRIT) method that penalizes the input variation in its criterion has been proposed. In this method, the PID parameters that are taken into stability can be calculated. The effectiveness of the proposed method is evaluated by an experimental result of a spiral heat, exchanger. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： process control PM control self tuning control data-driven control extended fictitious reference iterative tuning (E-FRIT)

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A robust NMPC scheme for semi-batch polymerization reactors

A robust NMPC scheme for semi-batch polymerization reactors

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Jang, Hong Lee, Jay H. Biegler, Lorenz T. Korea Adv Inst Sci & Technol Dept Biomol & Chem Engn 291 Daehak Ro Doejeon 34141 South Korea Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

A robust nonlinear model predictive control (NMPC) scheme is proposed for batch processes with multiple types of uncertainties Recently, economic MPC (eMPC) has attracted significant attention, particularly for batch process control given its flexibility in the cost function while addressing the nonlinear constrained multivariable dynamics seen in most batch processes. However, in the presence of various uncertainties such as parameter errors, external disturbances, and noise, performance of eMPC can deteriorate significantly as it tends to drive the system to limits of constraints. To achieve constraint satisfaction in the presence of common uncertainties, we propose a robust NMPC method based on multi-stage scenarios, state estimation;and back-off constraints. Performance of the proposed robust NMPC scheme is evaluated through an example of anionic propylene oxide polymerization reactor. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Robust nonlinear model predictive control Stochastic programming: State estimation Back-off constraint Batch process Polymerization reactor

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On the significance of the noise model for the performance of a linear MPC in closed-loop operation

On the significance of the noise model for the performance o...

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Hagdrup, Morten Boiroux, Dimitri Mahmoudi, Zeinab Madsen, Henrik Poulsen, Niels Kjolstad Poulsen, Bjarne Jorgensen, John Bagterp Tech Univ Denmark DTU Compute Lyngby Denmark Danish Diabet Acad Odense Denmark

This paper discusses the significance of the noise model for the performance of a Model Predictive controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Closed-loop control predictive control model based control Kalman Filters state estimation

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Dual MPC with Reinforcement Learning

Dual MPC with Reinforcement Learning

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11th IFAC symposium on dynamics and control of process systems including Biosystems

作者： Morinelly, Juan E. Ydstie, B. Erik Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

An adaptive optimal control algorithm for system with uncertain dynamics is formulated under a Reinforcement Learning framework. An embedded exploratory component, is included explicitly in the objective function of an output feedback receding horizon Model Predictive control problem. The optimization is formulated as a Quadratically Constrained Quadratic Program and it is solved to epsilon-global optimality. The iterative interaction between the action specified by the optimal solution and the approximation of cost functions balances the exploitation of current knowledge and the need for exploration. The proposed method is shown to converge to the optimal policy for a controllable discrete time linear plant with unknown output parameters. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Adaptive control dual control optimal control model predictive control reinforcement learning approximate dynamic programming

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