Articles
<![CDATA[Model Predictive Control System Design for Boiler Turbine Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>;
<![CDATA[Anamika Bhatia Jain]]>
<![CDATA[ International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 5: October 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijece.v5i5.pp1054-1061
<![CDATA[MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.]]>
<![CDATA[Model Predictive Control System Analysis for Sugarcane Crushing Mill Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>;
<![CDATA[Anamika Bhatia Jain]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 3: September 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v4i3.503
<![CDATA[MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In this paper the performance of an MPC controller on a single stage of milling train of sugar mill is analyzed. A linear model of the plant is taken with flap position and turbine speed set point as manipulated variables and mill torque and buffer chute height as controlled variables. The set point tracking responses are compared for constrained and unconstrained cases. The effect of presence of unmeasured disturbance also is investigated.]]>
<![CDATA[ANN Controller Design for Lime Kiln Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v4i4.514
<![CDATA[The lime kiln is a very complex multivariable process with severe non linearities, high degree of coupling and frequent disturbances. In this paper a 2x2 lime kiln process with two manipulated variables namely the fuel gas flowrate, and the percent opening of the induced draft damper and two controlled variables namely front end temperature and back end temperature has been considered. After its decoupling, artificial neural network (ANN) controllers have been designed to control the front end temperature. The performance of ANN controllers have been compared with that of conventional controllers.]]>
<![CDATA[ANN Controller Design for Lime Kiln Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v4i4.514
<![CDATA[The lime kiln is a very complex multivariable process with severe non linearities, high degree of coupling and frequent disturbances. In this paper a 2x2 lime kiln process with two manipulated variables namely the fuel gas flowrate, and the percent opening of the induced draft damper and two controlled variables namely front end temperature and back end temperature has been considered. After its decoupling, artificial neural network (ANN) controllers have been designed to control the front end temperature. The performance of ANN controllers have been compared with that of conventional controllers.]]>
<![CDATA[Model Predictive Control System Analysis for Sugarcane Crushing Mill Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>;
<![CDATA[Anamika Bhatia Jain]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 3: September 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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Full PDF (505.119 KB)
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DOI: 10.11591/eei.v4i3.503
<![CDATA[MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In this paper the performance of an MPC controller on a single stage of milling train of sugar mill is analyzed. A linear model of the plant is taken with flap position and turbine speed set point as manipulated variables and mill torque and buffer chute height as controlled variables. The set point tracking responses are compared for constrained and unconstrained cases. The effect of presence of unmeasured disturbance also is investigated.]]>
<![CDATA[Model Predictive Control System Analysis for Sugarcane Crushing Mill Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>;
<![CDATA[Anamika Bhatia Jain]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 3: September 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
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Original Source
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Check in Google Scholar
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Full PDF (505.119 KB)
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DOI: 10.11591/eei.v4i3.503
<![CDATA[MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In this paper the performance of an MPC controller on a single stage of milling train of sugar mill is analyzed. A linear model of the plant is taken with flap position and turbine speed set point as manipulated variables and mill torque and buffer chute height as controlled variables. The set point tracking responses are compared for constrained and unconstrained cases. The effect of presence of unmeasured disturbance also is investigated.]]>
<![CDATA[ANN Controller Design for Lime Kiln Process ]]>
<![CDATA[Sandeep Kumar Sunori]]>;
<![CDATA[Pradeep Kumar Juneja]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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Full PDF (1279.925 KB)
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DOI: 10.11591/eei.v4i4.514
<![CDATA[The lime kiln is a very complex multivariable process with severe non linearities, high degree of coupling and frequent disturbances. In this paper a 2x2 lime kiln process with two manipulated variables namely the fuel gas flowrate, and the percent opening of the induced draft damper and two controlled variables namely front end temperature and back end temperature has been considered. After its decoupling, artificial neural network (ANN) controllers have been designed to control the front end temperature. The performance of ANN controllers have been compared with that of conventional controllers.]]>
<![CDATA[Concentrating Power for MPPT Solar PV Module forming Channelization of Efficient Energy ]]>
<![CDATA[Pankaj Aswal]]>;
<![CDATA[Mayank Chaturvedi]]>;
<![CDATA[Puspender Singh]]>;
<![CDATA[Pradeep Kumar Juneja]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v4.i3.pp526-531
<![CDATA[The energy of photovoltaic (PV) is going to become a most relevant part of renewable energy in world, by PVC Cell system for sufficient energy extraction this research will scrutinize the solar PV energy generation and conversion by effective devices to grid alliances Here this treatise target on I-V and P-V characteristics of Photo volatile modules or array, primarily under irregular shading condition, the model development of PV system and considering both physical and electrical parameters of solar PV module. The treatise ponder that how disparate bypass diode collocation could be influences maximum power conclusion characteristics of a solar PV module or array.]]>
