Parameter estimation, modeling and IMC -PID control of flow-temperature using cascade control strategy

In industries it is necessary to monitor and control temperature in real time. Flow dependent temperature control has become vital in different industries like pharmaceuticals, drying, material processing and petroleum industries. This paper aims at nonlinear modeling, identification and control of a temperature-flow cascaded control system. The experimentally obtained open loop models are used to design conventional controllers for primary and secondary loops using Cohen-Coon tuning method. Both flow and temperature processes have also been modeled stochastically and with the help of ANN technique which have been validated with experimental data. The parameters of the model are estimated using Auto Regressive eXogenous (ARX) identification techniques. The conventional PI controller response is compared with Internal Model Control (IMC). Further the Integral Absolute Error (IAE) is computed separately for the conventional controller and the IMC controller to select better performance of controller. In the cascade loop, temperature process is kept in primary loop and flow is considered in the secondary loop. Results indicate that it can be implemented in commercial. Changes in the inlet flow of water to the heating tank affect the temperature of the process fluid directly and hence it is important to control the nonlinear behavior of the flow process in order to control the temperature process.