The usage of water treatment technologies is increasing at a rapid rate due to scarcity of pure water in the world. This paper proposes controller design using grey wolf optimization (GWO) algorithm for water treatment plants. Doha reverse osmosis (RO) water treatment plant is considered for the experimental purpose. Proportional-integral-derivative (PID) controller is designed for the considered Doha RO plant. The proposed method can minimize the error criterion in such a way that good transient responses for flux and conductivity are obtained. To show the efficacy of GWO based controller, other state-of-art optimization techniques are also used for tuning of controller parameters. Comparative simulations show that GWO algorithm is more efficient and suitable over other algorithms for tuning the parameters of controller for Doha RO water treatment plant.

Fresh water demand is growing drastically in many parts of the world. Desalination of seawater, brackish water, and waste water is one solution to meet the demands of fresh water. Currently, reverse osmosis (RO) desalination process is one of the best methods for the desalination process. In this study, a modified controller design is proposed for RO desalination system based on symbiotic organisms search (SOS) algorithm. A multivariable model of RO desalination plant is considered for experimentation. The RO system considered here is first decoupled using simplified decoupling process to obtain two non-interacting loops. Then, a proportional-integral-derivative controller with second order derivative (PID-DD) scheme based on SOS algorithm is proposed for each loop to find optimal control parameters of the RO system. To design the PID-DD controller for each loop, integral of squared error (ISE) is considered as fitness function. Four other state-of-the-art optimization algorithms, namely, teacher-learner-based-optimization (TLBO), differential evolution (DE), particle swarm optimization (PSO), and artificial bee colony (ABC), algorithms are also tested for the considered system. To show competitiveness of the proposed SOS-based PID-DD controller, a comparative study based on time domain analysis is performed. Results show the SOS-based PID-DD controller is superior to other PID-DD controllers.

This paper presents an efficient and fast tuning method of controller parameters for position control of DC servo motor. A control scheme for PID controller tuning is proposed here which is based on Luus-Jaakola Optimization. Luus-Jaakola optimization procedure is used to optimize large scale nonlinear optimization problems. The tuning of PID controllers is accomplished by minimizing the Integral-Square-Error (ISE). The ISE is minimized using the Luus-Jaakola (LJ) optimization algorithm. LJ optimization procedure is a simple, yet powerful method for optimization available in literature. The results of PID control using LJ method are compared with the Ziegler-Nichol's (ZN) tuning. The simulation results show that the LJ method performs better results than the ZN technique and can successfully be used for tuning of PID controllers for DC servo motor.