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A Causal Model-Based Scheduling Approach for Coke Oven Gas System in Steel Industry

IFAC-PapersOnLine 2018年第21期51卷 7-12页

作者： Jin, Feng Lv, Zheng Li, Maohua Mou, Lei Zhao, Jun Wang, Wei School of Control Science and Engineering Dalian University of Technology Dalian China Shanghai Baoneng Information Technology Co. Ltd China

Reasonable scheduling of coke oven gas (COG) in steel industry will save fossil energy resources and increase gas consumption efficiency. In this study, a causal model-based scheduling approach is proposed to provide guidance for the coke oven gas scheduling. The causal relationship of the variables related to the gas tank level is discovered and the causal diagram is established, according to which the training sample is constructed and the predicting model of gas tank level is trained. Then, an objective function that considers the scheduling solution and its result is designed. To calculate the most reasonable solution, a modified particle swarm optimization algorithm is employed. The validation experiments are carried out by using practical data coming from a steel plant in China, where the gas tank level approaching the higher and the lower level zones are both considered. The human experience-based method and a data-based scheduling one are conducted as comparative studies. The results indicate that the proposed method is efficient for COG scheduling. © 2018

关键词： Scheduling Air navigation Coke Coke ovens Energy resources Gases Industrial ovens Particle swarm optimization (PSO) Steelmaking Tanks (containers) Causal model Causal relationships Coke oven gas Comparative studies Experience based methods Fossil energy resources Modified particle swarm optimization algorithms objective functions

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Dynamic modeling of enzyme controlled metabolic networks using a receding time horizon

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IFAC-PapersOnLine 2018年第18期51卷 203-208页

作者： Lindhorst, Henning Reimers, Alexandra-M. Waldherr, Steffen Institute for Automation Engineering Otto-von-Guericke-Universität Magdeburg Germany Department of Mathematics and Computer Science Freie Universität Berlin Germany KU Leuven Department of Chemical Engineering Belgium

Microorganisms have developed complex regulatory features controlling their reaction and internal adaptation to changing environments. When modeling these organisms we usually do not have full understanding of the regulation and rely on substituting it with an optimization problem using a biologically reasonable objective function. The resulting constraint-based methods like the Flux Balance Analysis (FBA) and Resource Balance Analysis (RBA) have proven to be powerful tools to predict growth rates, by-products, and pathway usage for fixed environments. In this work, we focus on the dynamic enzyme-cost Flux Balance Analysis (deFBA), which models the environment, biomass products, and their composition dynamically and contains reaction rate constraints based on enzyme capacity. We extend the original deFBA formalism to include storage molecules and biomass-related maintenance costs. Furthermore, we present a novel usage of the receding prediction horizon as used in Model Predictive Control (MPC) in the deFBA framework, which we call the short-term deFBA (sdeFBA). This way we eliminate some mathematical artifacts arising from the formulation as an optimization problem and gain access to new applications in MPC schemes. A major contribution of this paper is a systematic approach for choosing the prediction horizon and identifying conditions to ensure solutions grow exponentially. We showcase the effects of using the sdeFBA with different horizons through a numerical example. © 2018

关键词： Cost benefit analysis Enzymes Forecasting Gene expression Linear programming Metabolic engineering Metabolism Model predictive control Predictive control systems Changing environment Constraint based method Flux balance analysis Linear optimization Metabolic network objective functions Optimization problems Prediction horizon

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Model Predictive Control of Marine Vessel Power System by Use of Structure Preserving Model ⁎

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IFAC-PapersOnLine 2018年第29期51卷 335-340页

作者： Dahl, Andreas Reason Thorat, Laxminarayan Skjetne, Roger Department of Marine Technology TrondheimNO-7491 Norway

The paper presents model predictive control (MPC) based on an optimization model drawn from the structure preserving model (SPM) for marine vessel power systems. Three objective functions are proposed to control frequency, transient load and power flow. The objective functions, in addition to a benchmark controller, are applied to a simulated power system. © 2018

关键词： Power control Electric load flow Electric power system control Model predictive control Power management Predictive control systems Standby power systems Control frequency Marine systems Marine vessels objective functions Optimization modeling Power system controls Structure preserving models Transient load

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Optimization Mathematical Modeling of the Weight of Metal Structure of Suspended Belt Conveyor Linear Section

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IFAC-PapersOnLine 2018年第30期51卷 616-619页

作者： Boslovyak, P.V. Emelyanova, G.A. Bauman Moscow State Technical University Moscow Russia Russia

At present, one may witness the development and improvement of conveyor transport, in particular, a specialized suspended belt conveyor with a load-carrying belt. The use of methods of reducing the mass of the conveyor metal structure is an urgent task at the initial stage of its design. A mathematical model of the linear section metal structure of the conveyor with a suspended load-carrying belt was developed. The undertaken research resulted in presenting the values of stresses and deflections appearing in the linear section metal structure of various designs, depending on different productivity of the suspended belt conveyor. Based on the studies performed, it was revealed that the use of modern approaches, in particular optimization approach, to the design of the conveyor metal structure allows improving the weight and dimensions of the entire conveyor. © 2016

关键词： Structural design Belt conveyors functions Mathematical models Metals Linear sections Load carrying Metal structures objective functions Optimal design Optimization approach Suspended loads

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Simple method for parameter identification of a nonlinear Greitzer compressor model

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IFAC-PapersOnLine 2018年第13期51卷 198-203页

作者： Backi, Christoph Josef Gravdahl, Jan Tommy Skogestad, Sigurd Trondheim7491 Norway Trondheim7491 Norway

This work introduces a simple method to estimate state variables and identify parameters of a nonlinear dynamic Greitzer compressor model. The observer is based upon an extended Kalman filter, which estimates the dynamic states as well as a subset of parameters. In a Monte-Carlo-fashioned approach, the remaining set of parameters is then identified by minimizing an objective function representing the error between the measured variables and their estimates. The developments are demonstrated in numerical simulations. © 2018

关键词： Parameter estimation Compressors Estimation Identification (control systems) Kalman filters Observability Compressor modeling objective functions SIMPLE method State variables

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Mathematical Model for the Home Health Care Scheduling and Routing Problem with Flexible Lunch Break Requirements

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IFAC-PapersOnLine 2018年第11期51卷 334-339页

作者： Xiao, Liyang Dridi, Mahjoub El Hassani, Amir Hajjam Nanomedicine Lab Univ. Bourgogne Franche-Comté UTBM BelfortF-90010 France

This paper formulates a mixed integer linear programming model of a home health care scheduling and routing problem with daily planning horizon. The entire procedure involves dispatching caregivers to serve visits demanded by patients at their homes with the objective function aims at minimizing the total operating cost. In some cases, based on the needs of patients, several caregivers should be synchronized and allocated to one patient under a given time window. The proposed model also accounts for multiple constraints such as the restricted working duration, the qualification and preference of patients, and innovative flexible lunch break requirements. Finally, the problem is solved to optimality by Gurobi, a commercial program solver. Numerical results shown that the solution performs quite well compared to the previous artificial planning collected in the Institute Montéclair, shows the the problems can be solved efficiently for optimal solutions. © 2018

关键词： Home health care Integer programming Scheduling Synchronization Lunch breaks Mixed integer linear programming model Multiple constraint Numerical results objective functions Optimal solutions Routing problems Scheduling and routing

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Optimal System Decomposition for Distributed Fault Detection: Insights and Numerical Results ⁎

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IFAC-PapersOnLine 2018年第24期51卷 578-585页

作者： Gei, Chiara Boem, Francesca Parisini, Thomas Dept. of Electronic and Electrical Engineering University College London United Kingdom Dept. of Electrical and Electronic Engineering Imperial College London United Kingdom KIOS Research and Innovation Centre of Excellence University of Cyprus Cyprus Dept. of Engineering and Architecture University of Trieste Italy

The paper deals with the problem of defining the optimal topology for a distributed fault detection architecture. A partition-based distributed fault detection method is considered based on the model of the system. The system is decomposed into subsystems and each subsystem is monitored by one local diagnoser. Non-overlapping decompositions are considered. A novel cost function is proposed to measure the detectability properties of a distributed fault detection method, depending on the topology of the detection framework. Different objective functions are taken into account and compared in order to analyze the influence of the decomposition on fault detection performance. Preliminary numerical results show that the minimization of the coupling between subsystems could not be always the best choice for the fault detection performance, and that the proposed cost function minimization allows the reduction of the detection time with the considered fault detection method. © 2018

关键词： Fault detection Cost functions Decomposition Numerical methods Topology Detection framework Detection performance Distributed fault detections Distributed systems objective functions Optimal decomposition Overlapping decomposition System decomposition

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Adaptive Sampling of Ocean Processes Using an AUV with a Gaussian Proxy Model

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IFAC-PapersOnLine 2018年第29期51卷 238-243页

作者： Berget, Gunhild Elisabeth Fossum, Trygve Olav Johansen, Tor Arne Eidsvik, Jo Rajan, Kanna Department of Engineering Cybernetics Center for Autonomous Marine Operations and Systems Norwegian University of Science and Technology Trondheim7491 Norway Department of Marine Technology Center for Autonomous Marine Operations and Systems Norwegian University of Science and Technology Trondheim7491 Norway Department of Mathematical Sciences Norwegian University of Science and Technology Trondheim7491 Norway

This paper presents methods for building and exploiting compact spatial models on board an autonomous underwater vehicle (AUV) towards tracking suspended material plumes. The research is aiming to improve real-time monitoring of dispersal dynamics connected to marine industries such as oil and mine tailing. By exploiting in-situ information from sensors, the AUV is able to assimilate and adapt the mission capitalizing on all the information available. The spatial model is built using Gaussian process approximations and an objective function for path planning is suggested to maximize the value of the collected information. © 2018

关键词： Autonomous underwater vehicles Gaussian distribution Gaussian noise (electronic) Marine industry Motion planning Oceanography Tailings Adaptive sampling Autonomous underwater vehicles (AUV) Gaussian Processes objective functions Real time monitoring Spatial modeling Spatial models Suspended material

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Design and Optimization of a Stator Turbine Blade profile using control parameters

Design and Optimization of a Stator Turbine Blade profile us...

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IEEE Aerospace Conference

作者： Gollapalli, Uday Chandra Chhavi, Chhavi SRM Univ Chennai 603203 Tamil Nadu India

ISBN: (纸本)9781538620144

The aerodynamic design of a turbine blade is very important to ensure proper flow deflection and acceleration. Profile generation of the blade plays a vital role in ensuring minimal losses and maximum performance. The aim is to design an optimized blade profile of a turbine stator blade which is efficient and can be used in the gas turbine industry. The mean line prediction method is used to decide the blade geometry and BLADEGEN software for profile generation. This method being a preliminary step gave a design based on the mean flow which was not sufficient for industrial purpose. Thus a study was performed on different control parameters like stagger angle, maximum thickness and other factors that have the greatest impact on the performance of the blade. The CFD results of the base case for the pressure distribution, profile losses, velocity and blade to blade velocity distribution were compared to the theoretical calculation for validation. The design variables were set as t/c ratio and stagger angle which were varied on the base profile for finding their best combination in order to get an optimized design that fulfills the objective functions, which were minimum profile loss and maximum outlet velocity. The CFD results were obtained using CFX-ANSYS for both the profiles. The profiles were compared on the basis of the objective functions to validate the optimization. The salient features of the new 2D profile of the stator turbine blade were highlighted and compared to the base profile.

关键词： turbine blade profile generation mean line prediction BLADEGEN control parameters design variables t/c ratio stagger angle objective functions CFX-ANSYS.

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Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

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Journal of Bioeconomics 2018年第2期20卷 183-211页

作者： Castro, Luz Maria Härtl, Fabian Ochoa, Santiago Calvas, Baltazar Izquierdo, Leonardo Knoke, Thomas Departamento de Economia Universidad Tecnica Particular de Loja San Cayetano s/n Loja Ecuador Institute of Forest Management Department of Ecology and Ecosystem Management TUM School of Life Sciences Weihenstephan Technische Universität München Hans-Carl-von-Carlowitz-Platz 2 Freising 85354 Germany Facultad de Ciencias Pecuarias Universidad Técnica Estatal de Quevedo Av. Carlos J. Arosemena 38 Quevedo Ecuador

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system;it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： objective functions Optimization System dynamics Time Uncertainty

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