Optimal design of FOPID Controller for the control of CSTR by using a novel hybrid metaheuristic algorithm

The escalating complexity in the process control industry emanates the demand for novel and advanced control techniques, which results in enhanced performance indices. A hybrid optimal control method i.e., FOPID control using chaotic state of matter search with elite opposition-based learning for controlling CSTR is proposed in this paper. Fractional order PID is a generalized form of PID Controller. It uses fractional calculus, resulting in a more flexible and better response accompanying rigorous adoption for substantially closed-loop system stability. Hybridization of SMS with chaotic maps and elite oppositional-based learning results in enhanced exploration capability along with randomization. In this paper, the results show that the CSMSEOBL tuned FOPID controller provides superior and optimum performance when compared to other metaheuristic algorithms.