Real-Time Implementation and Performance Analysis of a Novel SLADRC Hybrid Tuning Approach Using Graphical and Lichtenberg Optimization

Abstract

Optimizing the tuning parameters for a second-order linear active disturbance rejection controller (SLADRC) presents a challenge due to the complexity of system dynamics. This paper proposes a novel tuning method combining analytical, graphical, and optimization techniques. A graphical approach defines a feasible region based on gain margin and phase crossover frequency using a unified method, while a hybrid method integrating these rules with the Lichtenberg Optimization Algorithm precisely determines optimal parameters. The objective function of the proposed technique is formulated to minimize the deviations in desired settling time, overshoot, and disk margin. The proposed SLADRC tuning approach is evaluated through simulation on two benchmark systems and verified in real time on a DC motor position control system, employing two different loading arrangements. The proposed tuning achieves optimum performance with an average error of less than 0.1% within 30 iterations, and the resulting SLADRC outperforms PID and state feedback controllers under parameter uncertainties and external force disturbances in real time.