EMAPlus-optimized adaptive convergence prescribed performance control for high-precision steering of rack steering vehicles - Addie Irawan, Hashim; Norsharimie, Mat Adam; Mohd Iskandar Putra, Azahar; Mohd Zamri, Ibrahim; Mohd Herwan, Sulaiman (Institute of Physics, 2026)
This paper presents an optimal Adaptive Convergence Prescribed Performance control cascaded with Anti-Windup PI (ACPPC-API) controller for steering-position control of rack steering vehicles (RSV) operating on cornering paths, optimized using the proposed Enhanced Evolutionary Mating Algorithm Lite (EMAPlus). The ACPPC framework regulates steering-error evolution through dynamically shaped convergence envelopes, while the Anti-Windup PI (AW-PI) inner loop stabilizes actuator behavior under saturation constraints. EMAPlus is employed to jointly tune the ACPPC and AW-PI parameters, enabling fast, stable, and computationally efficient optimization compared with the original Evolutionary Mating Algorithm (EMA), Ant Lion Optimizer (ALO), and Grasshopper Optimization Algorithm (GOA). Simulation results demonstrate that the EMAPlus-tuned ACPPC–API controller achieves the highest steering-tracking accuracy, reducing overshoot by up to 64%, suppressing residual ripple to within ±0.02 radians, and improving settling time by 20%–35% relative to the benchmark optimizers. These performance gains translate into superior vehicle-level responses, including 30%–60% lower curvature-tracking error, 45%–65% smaller sideslip deviation, and smoother lateral–yaw coordination during cornering maneuvers. Actuator-level and ride-quality indicators further reveal 35%–60% reductions in peak road-wheel rate and lateral jerk. Energy analysis confirms that more than 80% of the lateral–yaw kinetic energy is effectively directed into productive lateral-velocity motion with a shortened transient duration. The results establish the EMAPlus-optimized ACPPC–API controller as an efficient and robust steering solution for high-precision RSV cornering applications.