Document Type : Research Article
Department of Instrumentation Engineering, Madras Institute of Technology Campus, Anna University, Chennai 6000444, Tamil Nadu, INDIA
Department of Chemical Engineering, CSIR-CLRI, Chennai 600025, Tamil Nadu, INDIA
Department of Instrumentation Department of Instrumentation Engineering, Madras Institute of Technology Campus, Anna University, Chennai 6000444, Tamil Nadu, INDIA
Multi Effect Evaporator (MEE) is an important unit operation in industrial waste effluent treatment where water recovered from MEE can be reused for industrial operations thus reducing fresh water demand of the industry leading to Zero Liquid Discharge (ZLD) and environmental sustainability. Economically, multi-effect evaporators in many industries are used to improve the steam economy and cut down the waste handling cost. In this study, a dynamic mathematical model for a seven-effect evaporator has been developed and the model is validated against the real-time data collected from an industrial evaporator available in the Common Effluent Treatment Plant (CETP) located at Pallavaram, Chennai, India. Parametric sensitivity analysis is carried out to study the effect of various input parameters on the concentration of the output stream. Parametric studies reveal that input parameters namely heat transfer coefficient and steam flow rate have more influence on the concentration of the output. Lyapunov-based MPC (LMPC) scheme is implemented to achieve important performance characteristics like a low salt concentration in the water discharge, disturbance rejection, and stability. The disturbance rejection efficiency of LMPC is tested by adding 1% positive disturbance in feed concentration. Also, stability is assessed by introducing an additional delay of 2 seconds in the process. The performance of LMPC is compared with other controllers like IMC-PID and MPC. The closed-loop performance of all the proposed controllers for MEE is evaluated using error criteria and settling time. In LMPC, ISE, IAE value,, and settling time are drastically reduced by 68.15%, 88.39%, and 21.79% respectively with respect to MPC. Thus better setpoint tracking, quicker settling time and better stabilization of product concentration will pave the way for ZLD and improved water quality of the recycled water.