Effective FOPID Control of High-Order Fractional Systems: An Improved ALO-Based Model Reduction Approach

Abstract This paper presents the optimistic design and testing of a fractional order PID (FOPID) controller for higher fractional order (HFO) systems. To mitigate the complexity associated with HFO models, a reduced fractional order (RFO) system was meticulously derived. This derivation employed an Improved Ant Lion Optimization (IALO) framework, specifically enhancing the adaptive shrinking of traps methodology. The RFO system's accuracy in representing the HFO dynamics was rigorously confirmed through comparative performance analyses using Integral Squared Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE) criteria. Furthermore, the FOPID controller's precise control capabilities were validated by comparing the time-domain specifications of both the HFO and RFO systems.