Design and Implementation of Controller for a Nonlinear Spherical Tank System using Soft computing Techniques

In this work, Particle Swarm Optimization (PSO) based intelligent controller design technique is attempted for a nonlinear spherical tank process. The search process is guided by an objective function, which considers the minimization of some key parameters such as Integral Square Error (ISE), Integral Absolute Error (IAE), and settling time (ts) of the process under study. The proposed controller tuning procedure is initially tested on the mathematical model of the spherical tank system with a chosen operating region. A detailed simulation study is also performed with the chosen operating regions in order to validate the performance of proposed controller design technique and the results are validated with fuzzy controller. The simulation results evident that, the PSO based PI controller offers better steady state response and performance indices for the considered operating region. Finally, the PSO tuned PI controller is implemented and tested on a laboratory scale real time nonlinear spherical tank system. The real-time responses evident that, proposed controller offers enhanced result for both reference tracking and disturbance rejection operations with an improved performance measure values..