Computational analysis of hybrid grey wolf and particle swarm optimization for water level control in coupled tank

Water level control at a precise set point is a major concern in process control systems such as bulk drug production industries. Loss in production at the initial stage is observed until the water level reaches desired level. Pharmaceutical industries can however be benefited if they could maintain the precise water level control at the initial stage of production with the help of the performance optimization using various techniques. To achieve optimized value of the selected performance index, a hybrid of particle swarm optimization (PSO) and grey wolf optimization (GWO) is found to provide the desired performance in the best possible manner. The mathematical model of the coupled tanks is first developed using the state space analysis which can then be converted to transfer function form so as to accomplish the simulation. In this paper, integral square error (ISE) is selected as the performance index for the minimization to improve overall performance of the system. Observations from the hybrid GWO-PSO optimization articulate that overshoot and settling time can be improved as per the industry needs. Performance evaluation of different optimization techniques is discussed in this paper.