TY - JOUR
T1 - Enhanced automatic voltage regulation using an extended PIDA controller optimised by the snake algorithm
AU - Chetty, Nelson Dhanpal
AU - Gandhi, Ravi
AU - Sharma, Gulshan
AU - Çelik, Emre
AU - Kumar, Rajesh
N1 - Publisher Copyright:
© 2025
PY - 2025/6
Y1 - 2025/6
N2 - Maintaining voltage stability within acceptable limits is crucial in power systems, with Automatic Voltage Regulation (AVR) ensuring consistent performance. Traditionally, PID controllers have been widely used; however, they struggle in complex, nonlinear environments with fluctuating conditions and disturbances. This study proposes an Extended PID-Acceleration (ePIDA) controller incorporating a novel state observer-based Disturbance Observer (DOB) for enhanced voltage regulation. The Snake Optimiser (SO) is introduced for the first time in AVR tuning, leveraging its dynamic leader-follower mechanism to achieve faster convergence and optimal controller gains. The SO-ePIDA framework extends the traditional PIDA structure with a three-degree-of-freedom (3DOF) approach, enhancing setpoint tracking and disturbance rejection. The proposed approach is evaluated against six widely used optimisation strategies through comparative statistical and graphical analyses, considering step-load variations and system parameter settings. Results demonstrate that the SO-ePIDA controller achieves a rise time of 0.1679 s, a settling time of 0.3123 s, and the lowest ISTAE value of 0.0046, ensuring superior transient response and steady-state accuracy. Furthermore, under a 30 % step-load disturbance, the proposed controller exhibits the fastest recovery time of 0.1065 s, significantly outperforming other methods. The AVR system was tested with ±25 % and ±50 % variations in system parameters to assess robustness under parametric uncertainty. The results confirm that the SO-ePIDA controller maintains stability, with rise time deviations limited to 0.1577 and 0.2004 s and ISTAE variations between 0.0116 and 0.1891, demonstrating strong adaptability under extreme operating conditions. These findings establish the SO-ePIDA framework as a robust, high-performance solution for real-world AVR applications.
AB - Maintaining voltage stability within acceptable limits is crucial in power systems, with Automatic Voltage Regulation (AVR) ensuring consistent performance. Traditionally, PID controllers have been widely used; however, they struggle in complex, nonlinear environments with fluctuating conditions and disturbances. This study proposes an Extended PID-Acceleration (ePIDA) controller incorporating a novel state observer-based Disturbance Observer (DOB) for enhanced voltage regulation. The Snake Optimiser (SO) is introduced for the first time in AVR tuning, leveraging its dynamic leader-follower mechanism to achieve faster convergence and optimal controller gains. The SO-ePIDA framework extends the traditional PIDA structure with a three-degree-of-freedom (3DOF) approach, enhancing setpoint tracking and disturbance rejection. The proposed approach is evaluated against six widely used optimisation strategies through comparative statistical and graphical analyses, considering step-load variations and system parameter settings. Results demonstrate that the SO-ePIDA controller achieves a rise time of 0.1679 s, a settling time of 0.3123 s, and the lowest ISTAE value of 0.0046, ensuring superior transient response and steady-state accuracy. Furthermore, under a 30 % step-load disturbance, the proposed controller exhibits the fastest recovery time of 0.1065 s, significantly outperforming other methods. The AVR system was tested with ±25 % and ±50 % variations in system parameters to assess robustness under parametric uncertainty. The results confirm that the SO-ePIDA controller maintains stability, with rise time deviations limited to 0.1577 and 0.2004 s and ISTAE variations between 0.0116 and 0.1891, demonstrating strong adaptability under extreme operating conditions. These findings establish the SO-ePIDA framework as a robust, high-performance solution for real-world AVR applications.
KW - Disturbance observer
KW - PIDa Controller
KW - Snake optimizer
KW - Voltage Regulation
UR - http://www.scopus.com/inward/record.url?scp=105004260859&partnerID=8YFLogxK
U2 - 10.1016/j.rineng.2025.105181
DO - 10.1016/j.rineng.2025.105181
M3 - Article
AN - SCOPUS:105004260859
SN - 2590-1230
VL - 26
JO - Results in Engineering
JF - Results in Engineering
M1 - 105181
ER -