This study addresses the optimization of control performance for automatic voltage regulator systems by proposing a fractional-order PIDD² (FOPIDD²) controller design method based on the hybrid Black-winged Kite Algorithm (BWOA). To overcome the challenges of complex parameter tuning and adaptability to high-dimensional nonlinear optimization in PID controllers, the BWOA integrates the precise search mechanism of the Black-winged Kite Algorithm (BKA) with the spiral encircling strategy of the Whale Optimization Algorithm (WOA). By dividing high-fitness individuals into subgroups for parallel optimization, combined with an elitism preservation mechanism and Levy flight perturbation, the BWOA effectively balances global exploration and local exploitation capabilities, preventing premature convergence. Furthermore, a multi-factor objective function is adopted to optimize the six parameters of the FOPIDD² controller. Numerical simulations in MATLAB evaluate the controller’s performance across multiple dimensions, including transient response, frequency-domain stability, trajectory tracking, parameter uncertainty, and disturbance rejection, with comparisons to other recent controllers. Simulation results demonstrate that the BWOA-FOPIDD² controller achieves superior performance in most metrics. Therefore, the proposed method provides an efficient hybrid optimization framework for AVR system controller design.

Many meta-heuristic algorithms have been used in designing PID controllers to control automatic voltage regulator (AVR) system. PIDD ² controller is a PID controller with second-order derivative gain. The Fireworks Whale Optimization Algorithm is an advanced metaheuristic algorithm that combines fireworks and whale optimization algorithms. It has good exploratory properties because it explores a large potential space and avoids premature local optima. This paper presents a PIDD ² controller for improving the performance of the AVR system using a hybrid whale optimization algorithm. The simulation results, divided into two parts based on whether the limitation of the excitation voltage is considered or not, include a detailed analysis of the proposed controller in terms of step response, stability analysis, trajectory tracking, parameter uncertainty, and rejection of disturbance. To demonstrate the effectiveness of the proposed controller of the AVR system, it was compared with the controllers in recent literature in each of the aforementioned terms. The proposed controller, in most comparisons, provides better results than other controllers. All these results demonstrate that the performance and robustness of the proposed controller are competitive.

A solution to address the issues of environmental light interference in Remote Photoplethysmography (rPPG) methods is proposed in this paper. First, signals from the face’s region of interest (ROI) and background noise signals are simultaneously collected, and the two signals are processed by a differential to obtain a more accurate rPPG signal. This method effectively suppresses background noise and enhances signal quality. Secondly, the singular spectrum analysis algorithm (SSA) is enhanced to further improve the accuracy of heart rate detection. The algorithm’s parameters are adaptively optimized by integrating the spectral and periodic characteristics of the heart rate signal. Experimental results demonstrate that the method proposed in this paper effectively mitigates the effects of lighting changes on heart rate detection, thereby enhancing detection accuracy. Overall, the experiments indicate that the proposed method significantly improves the effectiveness and accuracy of heart rate detection, achieving a high level of consistency with existing contact-based detection methods.