Adaptive Control Methods for Interacting Conical Tank Processes Using Optimization Algorithm

The conical tanks are a nonlinear system that are used widely in different industries. The process of maintaining the levels of the tank is very complex and always controlled through the controller unit. The most common controller units are built with Proportional-Integral-Derivative (PID) or Proportional-Integral (PI) controllers. The improper tuning of PI controllers provides inadequate results and the system is subjected to settling time and overshoot issues. In the present work, the Optimized gain schedule PI controller is established to effectively control the nonlinear conical tanks. The tuning parameters of PI controller are optimized using the novel Hybrid optimization algorithm, which integrates the Particle Swarm algorithm (PSO) and the Golden Jackal (GJ) algorithm. The system is simulated using MATLAB. The set point and two regions are established, and the simulation is carried out to measure the step response and liquid level over the period. The rising time, settling time for the coupled tank system is identified to be 0.2197 s and 0.3912 s respectively. The optimized GSCPI (OGSCPI) controller performance is compared to the PSO based GSCPI and GJO based GSCPI controllers. The proposed OGSCPI controller outperformed the other controller and was found to be effective.