RT Journal Article
T1 Nature–Inspired Metaheuristic Optimization for Control Tuning of Complex Systems
A1 Garicano-Mena, Jesús
A1 Santos Peñas, Matilde
AB In this contribution, a methodology for the optimal tuning of controllers of complex systems based on meta–heuristic techniques is proposed. Two bio-inspired meta-heuristic optimization algorithms –the Antlion Optimizer (ALO) and the Whale Optimization Algorithm (WOA)– have been applied to two different dynamic systems: the Hoop & Ball electromechanical system, a system where a linearized description is adequate; and to a Wind Turbine–Generator–Rectifier, as an example of a complex non-linear dynamic system. The performance of the ALO and WOA techniques for the tuning of conventional PID controllers is evaluated in relation to the number of agents 𝑛𝑆 and the maximum number of iterations 𝑛𝑀𝑎𝑥𝐼𝑡𝑒𝑟; given the stochastic nature of both methods, repeatability is also addressed. Finally, the computational effort required for their implementation is considered. By analyzing the obtained metrics, it is observed that both methods provide comparable results for the two systems considered and, therefore, the ALO and WOA techniques can complement each other by exploiting the advantages of each of them in controller tuning.
PB Mdpi
YR 2024
FD 2024-12-30
LK https://hdl.handle.net/20.500.14352/113283
UL https://hdl.handle.net/20.500.14352/113283
LA eng
NO Garicano-Mena, J., & Santos, M. (2024). Nature–Inspired Metaheuristic Optimization for Control Tuning of Complex Systems. Biomimetics, 10(1), 13.
DS Docta Complutense
RD 15 abr 2025