In this paper, a single-stage pilot-scale RO (Reverse Osmosis) process is considered. The process is mainly used in various chemical industries such as dye, pharmaceutical, Beverage, and so on. Initially, mathematical modeling of the process is to be done followed by linearization of the system. Here a dual loop construction with a master and a slave is used. The slave uses the conventional PID (Proportional Integral Derivative) with a reference model of the RO process and the master uses the FOPID (Fractional Order Proportional Integral Derivative) with a real time RO process. The slave's output is compared with output of the real time RO process to obtain the error which is in turn used to tune the master. The slave controller is tuned using Ziegler Nicholas method and the error criterion such as IAE (Integral Absolute Error), ISE (Integral Squared Error), ITSE (Integral Time Squared Error), ITAE (Integral Time Absolute Error) are calculated and the minimum among them was chosen as the objective function for the master loop tuning. Hence the tuning of the controller becomes a whole. Therefore two optimization techniques such as PSO (Particle Swarm Optimization) and Bacterial Foraging Optimization Algorithm (BFO) are used for the tuning of the master loop. From the calculations the ITSE was having the minimum value among the performance indices hence it was used as the objective function for the BFO and PSO. The best-tuned values will be obtained with the use of these techniques and the best among all can be considered for various industrial applications. Finally, the performance of the process is compared with both techniques and BFO outperforms the PSO from the simulations.

A continuous stirred tank reactor (CSTR) is a batch reactor fortified with an impeller or additional mixing device to provide resourceful mixing. In chemical engineering, the name CSTR is often used to describe an idealised agitated tank reactor used to model manoeuvre variables necessary to achieve a specified output. Most chemical plants have a process involving a continuous stirred tank reactor (CSTR), and it has more nonlinearity in real-world implementation due to disturbances like change in surrounding temperature, nonuniformity in mixing, and change in the temperature of the coolant. The aim of the work is to study the dynamic behaviour of a continuous stirred tank reactor with coolant flow rate as input and reactor temperature as output and to design a suitable controller to control the temperature of the continuous stirred tank reactor by conducting an exothermic reaction in real-time. A continuous stirred tank reactor was modelled with the help of a transfer function model in the MATLAB environment. For controlling the temperature of the reactor fluid, the design of proportional integral derivative, proportional integral derivative (PID) -particle swarm optimization (PSO), proportional integral derivative (PID) -artificial bee colony optimization (ABC) and model predictive control (MPC) controller were carried out. The simulation results show that model predictive control has better tracking performance compared to conventional PID, PID-PSO or PID-ABC.