A VNS algorithm for PID controller : hardware-in-the-loop approach.
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Date
2021
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Abstract
Tuning the Proportional Integral Derivative, or PID, controller in cyber-physical systems is a major challenge as it requires advanced mathematical skills. Several authors in the literature have shown that optimization algorithms are efficient for auto-adjust PID controller constants, especially when there is no mathematical modeling. However, the literature lacks works that show the efficiency of the Variable Neighborhood Search (VNS) algorithm to auto-adjust the PID. In this work, we investigate the efficiency of the Variable Neighborhood Algorithm to fine-tune a PID controller of a real cyber physical-system: a birotor flying drone. The approach consists of applying a numerical neighborhood structure to optimize the three constants of the PID, according to a proposed fitness function. Experiments reveal the feasibility of fine-tuning the PID controller and the birotor balancing with the Variable Neighborhood Algorithm with reduced time.
We compared the VNS-approach against one based on genetic algorithms, and on average, the VNS-approach achieves better results with lower computational and memory costs. Results suggest that the approach may be used in real or commercial systems, helping to fine-tune the controller to new environment changes or even last-minute project modifications.
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Keywords
Variable neighborhood search - VNS, Cyber-physical systems, Proportional integral derivative, Self-tuning, Hardware-in-the-loop
Citation
SILVA, G. A. L . et al. A VNS algorithm for PID controller: hardware-in-the-loop approach. IEEE Latin America Transactions, v. 100, n. 9, mar./set. 2021. Disponível em: <https://latamt.ieeer9.org/index.php/transactions/article/view/4831>. Acesso em: 12 set. 2021.