32 research outputs found

    Issues Faced in a Remote Instrumentation Laboratory

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    An Online Lab is a multi-university shared laboratory environment, where students can exercise their knowledge as they would do in a physical lab. The idea is to have maximum resource utilization and collaboration between universities by sharing of ideas. This kind of remote laboratory negates the economic issues to set up a laboratory and allows every student to have an experience of real laboratory. As part of Ministry of Human Resource Development (MHRD) Robotics Lab project a study on state of art of remote labs was conducted. This paper discusses some key issues in the design and operation of such remote labs. The lab should be remotely usable by a large student body, with varied levels of sophistication, all the way from elementary learners, to PhD students doing research. In addition, the high design load implies that the architecture should be highly parallel, and structurally reliable

    The OpenModelica integrated environment for modeling, simulation, and model-based development

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    OpenModelica is a unique large-scale integrated open-source Modelica- and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica- UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.Fil: Fritzson, Peter. Linköping University; SueciaFil: Pop, Adrian. Linköping University; SueciaFil: Abdelhak, Karim. Fachhochschule Bielefeld; AlemaniaFil: Asghar, Adeel. Linköping University; SueciaFil: Bachmann, Bernhard. Fachhochschule Bielefeld; AlemaniaFil: Braun, Willi. Fachhochschule Bielefeld; AlemaniaFil: Bouskela, Daniel. Electricité de France; FranciaFil: Braun, Robert. Linköping University; SueciaFil: Buffoni, Lena. Linköping University; SueciaFil: Casella, Francesco. Politecnico di Milano; ItaliaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Franke, Rüdiger. Abb Group; AlemaniaFil: Fritzson, Dag. Linköping University; SueciaFil: Gebremedhin, Mahder. Linköping University; SueciaFil: Heuermann, Andreas. Linköping University; SueciaFil: Lie, Bernt. University of South-Eastern Norway; NoruegaFil: Mengist, Alachew. Linköping University; SueciaFil: Mikelsons, Lars. Linköping University; SueciaFil: Moudgalya, Kannan. Indian Institute Of Technology Bombay; IndiaFil: Ochel, Lennart. Linköping University; SueciaFil: Palanisamy, Arunkumar. Linköping University; SueciaFil: Ruge, Vitalij. Fachhochschule Bielefeld; AlemaniaFil: Schamai, Wladimir. Danfoss Power Solutions GmbH & Co; AlemaniaFil: Sjolund, Martin. Linköping University; SueciaFil: Thiele, Bernhard. Linköping University; SueciaFil: Tinnerholm, John. Linköping University; SueciaFil: Ostlund, Per. Linköping University; Sueci

    Digital control

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    Prioritized Model Predictive Control for Quadruple Tank System

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    by A. T. Markana, Nitin Padhiyar and K. Moudgaly

    Multi-criterion control of a bioprocess in fed-batch reactor using EKF based economic model predictive control

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    This research paper presents an offline and online user defined priority driven multi-objective optimal control study of a bioprocess in a fed-batch reactor. Productivity and the amount of substrates used in the process are considered as the two control objectives in that order of priority for this purpose. The priorities in the objective functions are realized using the lexicographic approach by sequentially solving multiple objectives to arrive at a Pareto solution point. This approach is not sensitive to the tuning of weighting parameters as compared to the scalarized objective, practiced conventionally. The weighting factors tuning issue is demonstrated with an offline optimal control. The lexicographic optimization approach is then implemented to overcome this thing issue. Subsequently, the online optimal control problem is solved using economic model predictive control (EMPC) owing to the economic nature of the control objectives. Often, the Pareto curve is such that marginally relaxing one objective results into a significant improvement in the other objective. This can easily be implemented with the lexicographic approach and is demonstrated using EMPC. Moreover, unlike the continuous processes, the batch processes operate for a specific batch time. Hence, the shrinking horizon approach along with the EMPC framework is employed in the fed-batch bioreactor for online control with extended Kalman filter (EKF).by Markana Anilkumar, Nitin Padhiyar and Kannan Moudgaly

    Multi-objective control of a fed-batch bioreactor using shrinking horizon MPC: a case study

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    by Anilkumar Markana, Nitin Padhiyar and Kannan Moudgaly
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