TY - JOUR
T1 - Particle swarm optimization solution for roll-off control in radiofrequency ablation of liver tumors
T2 - Optimal search for PID controller tuning
AU - Faria, Rafael Mendes
AU - de Siqueira Rodrigues Fleury Rosa, Suélia
AU - Adolfo Marcelino de Almeida Nunes, Gustavo
AU - Silva Santos, Klériston
AU - Pissinati de Souza, Rafael
AU - Daniela Ibarra Benavides, Angie
AU - Kathariny de Oliveira Alves, Angélica
AU - Karoline Almeida da Silva, Ana
AU - Fabrício Rosa, Mario
AU - Aureliano de Anicêsio Cardoso, Antônio
AU - de Sousa Faria, Sylvia
AU - Berjano, Enrique
AU - Ferreira da Rocha, Adson
AU - dos Santos, Ícaro
AU - González-Suárez, Ana
N1 - Publisher Copyright:
© 2024 Faria et al.
PY - 2024/6
Y1 - 2024/6
N2 - The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value << 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques.
AB - The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value << 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques.
UR - https://www.scopus.com/pages/publications/85196948273
U2 - 10.1371/journal.pone.0300445
DO - 10.1371/journal.pone.0300445
M3 - Article
SN - 1932-6203
VL - 19
JO - PLoS ONE
JF - PLoS ONE
IS - 6 June
M1 - e0300445
ER -
