Gain scheduled particle swarm optimization based internal model control for tank level system

The proposed work attempts gain scheduled particle swarm optimization (PSO) based internal model control (IMC) for tank level process. IMC requires determining a single parameter , the filter constant. Optimal value of the filter constant is determined using PSO, an evolutionary technique. The tank process is nonlinear in nature. Model and inverse model are found for each linear region separately and clubbed together using a gain scheduler. The performance of the proposed controller shows the suitability of using it for the servo and regulatory control of nonlinear process.