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Papers by Kamesh Reddi
The present study focuses on the development of different cascade control configurations for temp... more The present study focuses on the development of different cascade control configurations for temperature control of a multiproduct semibatch polymerization reactor. The master controller regulates the reactor temperature by manipulating the mean cooling jacket temperature, whereas the slave controller manipulates the valve opening to control the mean jacket temperature. The configurations explored are based on generic model control (GMC) and proportional integral (PI) control. The effects of different controller tuning parameters are evaluated. The effect of other unmeasured and measured disturbances, i.e., impurity factor, monomer feed flow rate, and presence of measurement noise on control performance, is evaluated for two products A and B. GMC−GMC has shown better controller performance in terms of temperature tracking with minimum root-mean-square output deviation (RMSOD) values as well as minimum normalized root-mean-square input deviation (NRMSID) values from the nominal input value, compared to GMC−PI, PI−GMC, and PI−PI.
Gas chromatography -specifically gas-liquid chromatography -involves a sample being vapourised an... more Gas chromatography -specifically gas-liquid chromatography -involves a sample being vapourised and injected onto the head of the chromatographic column. The sample is transported through the column by the flow of inert, gaseous mobile phase. The column itself contains a liquid stationary phase which is adsorbed onto the surface of an inert solid In gas chromatography, the mobile phase (or "moving phase") is a carrier gas, usually an inert gas such as helium or an unreactive gas such as nitrogen. The stationary phase is a microscopic layer of liquid or polymer on an inert solid support, inside a piece of glass or metal tubing called a column (a homage to the fractionating column used in distillation). The instrument used to perform gas chromatography is called a gas chromatograph (or "aerograph").
Conference Presentations by Kamesh Reddi
— Polymerization processes are characterized by exothermic reactions with complicated nonlinear d... more — Polymerization processes are characterized by exothermic reactions with complicated nonlinear dynamics, especially in batch / semi-batch mode. The complexities of the polymerization kinetics and reactor behaviour pose difficult quality control problems. Therefore a control strategy that ensures an optimal as well as robust operation of polymerization reactors, under the influence of various disturbances control, is required to achieve the desired product specifications. It is extremely important to develop efficient methods for the synthesis of polymerization control strategies. In this work, the optimal target values of molecular weight and copolymer composition for a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor are set as set point trajectories and are tracked by PI controllers. Two versions of PI control, namely two independent SISO controllers and multivariable PI controller are attempted in this study for control of molecular weight and copolymer composition using coolant temperature and inlet feeding flow rate as manipulated inputs. This approach overcomes the drawbacks of open loop optimal control implementation though handling of the effects of load disturbances as well as set point changes. The simulation results demonstrate the usability of this approach for online optimization and control.
— In the present work, an adaptive Artificial Neural Network (ANN) model based Generic Model Cont... more — In the present work, an adaptive Artificial Neural Network (ANN) model based Generic Model Control (GMC) [ANNGMC] scheme is proposed for nonlinear processes. The proposed scheme consists of online parameter estimation of a purely data driven ANN model based on past measurements using Extended Kalman Filter, and control computation based on minimizing the deviation of predicted model output derivative from its desired reference trajectory in a GMC frame work. An industrial case study for temperature control of a multi-product semi-batch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANNGMC strategy at supervisory level, as cascade control configuration along with Proportional Integral (PI) controller i.e. ANNGMC-PI. The effect of batch to batch variations in terms of heat transfer variations, and some unmeasured disturbances i.e. impurity factor and monomer feed flow rate on control performance are evaluated for two products A and B. ANNGMC-PI control configuration has shown better controller performance in terms of temperature tracking with minimum root mean square output deviation (RMSOD) values as well as minimum normalized root mean square input deviation (NRMSID) values from the nominal input value compared to the standard PI-PI control scheme. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.
The present study focuses on the development of different cascade control configurations for temp... more The present study focuses on the development of different cascade control configurations for temperature control of a multiproduct semibatch polymerization reactor. The master controller regulates the reactor temperature by manipulating the mean cooling jacket temperature, whereas the slave controller manipulates the valve opening to control the mean jacket temperature. The configurations explored are based on generic model control (GMC) and proportional integral (PI) control. The effects of different controller tuning parameters are evaluated. The effect of other unmeasured and measured disturbances, i.e., impurity factor, monomer feed flow rate, and presence of measurement noise on control performance, is evaluated for two products A and B. GMC−GMC has shown better controller performance in terms of temperature tracking with minimum root-mean-square output deviation (RMSOD) values as well as minimum normalized root-mean-square input deviation (NRMSID) values from the nominal input value, compared to GMC−PI, PI−GMC, and PI−PI.
Gas chromatography -specifically gas-liquid chromatography -involves a sample being vapourised an... more Gas chromatography -specifically gas-liquid chromatography -involves a sample being vapourised and injected onto the head of the chromatographic column. The sample is transported through the column by the flow of inert, gaseous mobile phase. The column itself contains a liquid stationary phase which is adsorbed onto the surface of an inert solid In gas chromatography, the mobile phase (or "moving phase") is a carrier gas, usually an inert gas such as helium or an unreactive gas such as nitrogen. The stationary phase is a microscopic layer of liquid or polymer on an inert solid support, inside a piece of glass or metal tubing called a column (a homage to the fractionating column used in distillation). The instrument used to perform gas chromatography is called a gas chromatograph (or "aerograph").
— Polymerization processes are characterized by exothermic reactions with complicated nonlinear d... more — Polymerization processes are characterized by exothermic reactions with complicated nonlinear dynamics, especially in batch / semi-batch mode. The complexities of the polymerization kinetics and reactor behaviour pose difficult quality control problems. Therefore a control strategy that ensures an optimal as well as robust operation of polymerization reactors, under the influence of various disturbances control, is required to achieve the desired product specifications. It is extremely important to develop efficient methods for the synthesis of polymerization control strategies. In this work, the optimal target values of molecular weight and copolymer composition for a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor are set as set point trajectories and are tracked by PI controllers. Two versions of PI control, namely two independent SISO controllers and multivariable PI controller are attempted in this study for control of molecular weight and copolymer composition using coolant temperature and inlet feeding flow rate as manipulated inputs. This approach overcomes the drawbacks of open loop optimal control implementation though handling of the effects of load disturbances as well as set point changes. The simulation results demonstrate the usability of this approach for online optimization and control.
— In the present work, an adaptive Artificial Neural Network (ANN) model based Generic Model Cont... more — In the present work, an adaptive Artificial Neural Network (ANN) model based Generic Model Control (GMC) [ANNGMC] scheme is proposed for nonlinear processes. The proposed scheme consists of online parameter estimation of a purely data driven ANN model based on past measurements using Extended Kalman Filter, and control computation based on minimizing the deviation of predicted model output derivative from its desired reference trajectory in a GMC frame work. An industrial case study for temperature control of a multi-product semi-batch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANNGMC strategy at supervisory level, as cascade control configuration along with Proportional Integral (PI) controller i.e. ANNGMC-PI. The effect of batch to batch variations in terms of heat transfer variations, and some unmeasured disturbances i.e. impurity factor and monomer feed flow rate on control performance are evaluated for two products A and B. ANNGMC-PI control configuration has shown better controller performance in terms of temperature tracking with minimum root mean square output deviation (RMSOD) values as well as minimum normalized root mean square input deviation (NRMSID) values from the nominal input value compared to the standard PI-PI control scheme. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.