Temperature Control of Continuous Stirred Tank Reactor Using Model Predictive Controller Anurag (original) (raw)

Mathematical modeling and simulation of control strategies for continuous stirrer tank reactor

Bangladesh Journal of Scientific and Industrial Research

This study aims to establish a mathematical model for the Continuous Stirred Tank Reactor (CSTR) reactor that exhibits highly nonlinear dynamics and was carried out implemented by model-based conventional and non-conventional controllers for temperature control. The developed controllers were Proportional, Proportional-Integral, Proportional-Derivative, Proportional-Integral-Derivative, Two Degrees of Freedom, and Model Predictive Controller. Then, the controllers were simulated, tuning, and optimized using MatlabĀ®/SimulinkĀ®. The response results were compared and the analysis performed. The results indicated that the performance of 2-DOF-PID and MPC controllers is better than other conventional controllers for nonlinear systems such as the CSTR process. Bangladesh J. Sci. Ind. Res. 57(3), 149-162, 2022

Design of an Adaptive Predictive Controller for a Continuous Stirred Tank Reactor

An adaptive predictive controller has been designed in this paper. The model predictive controller design is based on the linear model and by employing adaptation mechanism; it can be applied to the nonlinear systems. Identification of the linear model parameters in each sample time from a recursive least square method is the suggested technique for adaptation. This method is applied to a CSTR1 as a nonlinear MIMO system with considering measurable disturbances. Simulations are performed for normal operating condition and a case in which system is caused with disturbance.

A comparison of nonlinear control techniques for continuous stirred tank reactors

1992

Globally linearixi ng control, a differential geometry-based technique (continuous), and nonlinear predictive conuol, an optimization-based approach (discrete), are compared for temperature control of a classical exothermic CSTR The two strategies can be tuned to have identical performance for setpoint changes or measured disturbances when there are no bounds on the manipulated variable. As the sample time is deca the two performance for unmeasured disturbances or uncertain models. approaches also yield identical However, NLFC pc4fom18 beater in the presence of constraints on the manipulated variable. An open-loop observer for the unmcasurcd state variable (composition) has been used. The system studied is minimum-phase, allowing a filtered deadbeat control law for the nonlinear predictive control strategy. MOTIVATION Chemical reactors create some of the most challenging feedback control problems faced by chemical process control engineers. Complex static and dynamic behavior, such as input or output multiplicities, ignition-extinction behavior and parametric sensitivity create challenges that are tough for traditional linear controllers to handle. An excellent review of multiplicities and instabilities in chemical reacting systems is provided by Raxon and Schmitx (1987). During the past five years there have been a number of control strategies developed that are based explicitly on a nonlinear process model. These nonlinear control strategies can be conveniently lumped into two categories: (i) differential geometry-based control and (ii) optimization-based control. A tutorial review of differential geometry-based control techniques has been provided by Kravaris and Kantor (1990); a comprehensive review of nonlinear control is presentedby Bequette (1991).

IJERT-Model predictive control for interactive thermal process

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/model-predictive-control-for-interactive-thermal-process https://www.ijert.org/research/model-predictive-control-for-interactive-thermal-process-IJERTV2IS110435.pdf In industries now a day the control of chemical process is important craft. Mostly all the chemical process are highly nonlinear in nature this cause instability of the process. This paper deals with basic simulation studies on of the interactive thermal process. The Combination processes Continuous stirred tank reactor (CSTR) and heat exchanger were controlled and the mathematical model was developed. This paper deals with the performance evaluation on the comparison of Model predictive control and conventional control in interactive thermal process. In the design of adaptive control, Model predictive control (MPC) scheme is used, in which the prediction method have been applied.A simulation is carried out using matlab. The control was performed to the combined process system using both the predictive control algorithm and conventional controller method and its results were analyzed. Thus it shows that the predictive controller will be suitable for this process then the conventional controller even without parameters change in the process. In a real world situation, these parameters could be estimated by using simulations or real execution of the system. Thus by controlling this process we recycle the waste heat and achieve less power consumption in the industries. Keywords- Process control - CSTR & Heat Exchanger, PID controller, MPC(Model Predictive control),Matlab.

Application of Predictive Control to a Batch Reactor

2003

The REPSOL company had in mind the improvement of the control on one of their chemical reactors. A feasibility study for the implementation of an Advanced Control technique (Predictive Control for temperature control for chemical Reactors PCR) for a batch reactor for Polyols production has been performed. The proposed technique PCR is based on a dynamic model of the unit which makes the prediction of the process variables behaviour. That behaviour is specified in terms of closed loop time response through a desired future trajectory. The control system shows a substantial improvement in the reactor temperature controllability and a notorious elimination of the competition between the cooling and heating actuators. The improvement is partially explained by the distinction made by the model and the control modules between the heating and the cooling dynamic effects which are usually quite different. Among the origins of the benefits obtained by such a model based predictive control, e...

Fuzzy Logic Based Temperature Control of Continuous Stirred Tank Reactor

CSTR (Continuous Stirred Tank Reactor) is an important subject in chemical process and provide a wide range of research in the field of control and instrumentation engineering and chemical engineering. Various controllers have been applied on the process (CSTR) to control the temperature. This paper shows the analysis of response of conventional PID controller and Fuzzy Logic used in Mamdani type of Controller for Temperature control of CSTR in the presence of disturbances acting on it. Mathematical model of CSTR (Continuous Stirred Tank Reactor) is developed by the set of differential equations.

Controller design based on Model Predictive Control for a nonlinear process

2012 8th International Symposium on Mechatronics and its Applications, 2012

Nowadays process industries require accurate, efficient and flexible operation of the plants. The need for development of innovative technologies for process modeling, dynamic trajectory optimization and high performance industrial process control is always a challenge. The process considered for modeling is a conical tank liquid level system. Control of liquid level in a conical tank is nonlinear due to the variation in the area of cross section with change in shape. Black box modeling is used to identify the system, which is identified to be nonlinear and approximated to be a First Order Plus Dead Time (FOPDT) model. Here the controller design is compared based on conventional Proportional Integral (PI) based on Skogestad's settings with Model Predictive Control (MPC).

COMPARISON OF PID AND MPC CONTROLLERS FOR CONTINUOUS STIRRED TANK REACTOR (CSTR) CONCENTRATION CONTROL

irjmets, 2020

Continuous Stirred Tank Reactor (CSTR) is amajorarea in process, chemical and control engineering. In this paper, PID and MPC controllers are designed for CSTR in order to analyze the output concentration of the system by comparing the two proposed systems using Matlab/Simulink. Comparison have been made using two desired concentration input (Random reference and step) signals with and without input side disturbance (Flow rate error). The simulation result shows that the continuous stirred tank reactor with MPC controller have better response in minimizing the overshoot and tracking the desired concentration for the system without input disturbance and with the effect of the disturbance makes the continuous stirred tank reactor with MPC controller output with small fluctuations and still better than the continuous stirred tank reactor with PID controller. Finally the comparative analysis and simulation results prove the effectiveness of the continuous stirred tank reactor with MPC controller.

Design and Implementation of PI and PIFL Controllers for Continuous Stirred Tank Reactor System

2014

Continuous stirred tank reactor system (CSTR) is a typical chemical reactor system with complex nonlinear characteristics where an efficient control of the product concentration in CSTR can be achieved only through accurate model. The mathematical model of the system was derived. Then, the linear model was derived from the nonlinear model. A conventional PI controller and PI fuzzy logic controller for continuous stirred tank reactor are proposed to control the concentration of the linear CSTR. The simulation study has been curried out in MATLAB SIMULINK workspace. The best controller has been chosen by comparing the criteria of the response such as settling time, rise time, percentage of overshoot and steady state error. From the simulation result the PIFL controller has a better performance than conventional PI controller.