SCHO-Optimized Fractional-Order Control Strategy for Enhanced Alternator Voltage Stability
This paper proposes a novel metaheuristic optimization framework grounded in the mathematical properties of hyperbolic trigonometric functions, introducing the Sinh–Cosh Optimizer (SCHO) as a bio-inspired algorithm that leverages the inherent gradient-like dynamics of sinh and cosh operators to achieve a principled and adaptive equilibrium between global exploration and local exploitation across complex search landscapes. The proposed framework is applied to tune an incommensurate Fractional-Order PID (FOPID) controller for Automatic Voltage Regulator (AVR) systems, where nonlinear dynamics and parametric uncertainties pose critical control challenges. The incommensurate non-integer differintegral structure extends the controller's degrees of freedom, enhancing its capacity to handle memory-dependent system behavior. Comparative simulations against conventional PID and standard FOPID benchmarks demonstrate a 32.115% overshoot reduction and a 33.335% ITSE improvement, with sustained robustness under load disturbances and parametric perturbations. The SCHO–FOPID strategy offers a scalable and mathematically rigorous intelligent control solution for uncertain nonlinear power systems, with direct applicability to smart grid and renewable energy contexts.