Fine-Tuned Design of the PIDFFD2F Control Strategy for the Functional Electrical Stimulation System Using Dandelion Optimizer

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Date

2025

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Elsevier Science Ltd

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Abstract

Functional Electrical Stimulation (FES) is a therapeutic and rehabilitative technique that uses electrical currents to stimulate nerves and muscles. This technology is vital in a wide range of medical applications, particularly for people with neurological disorders, paralysis or other conditions that affect muscle function. On the other hand, the complexity of human neuromuscular responses requires the design of a control structure that can dynamically adapt to changing conditions to ensure effective and safe stimulation. Therefore, this paper proposes proportional-integral-derivative with fractional order derivative filter plus double derivative with filter (PIDFFD2F) and proportional-integral-derivative with fractional order derivative filter (PIDFF) control structures to improve the performance of a FES system. The fine-tuning of the parameters in the proposed control structures is achieved by an efficient and effective algorithm, the Dandelion Optimizer (DO). The effectiveness of the DO-PIDFFD2F and DO-PIDFF controllers on the FES system has been thoroughly investigated through a series of tests and analyses, encompassing aspects such as transient response, Bode analysis, rejection of external disturbances, handling of measurement sensor noise, adaptability to parameter changes, responsiveness to reference changes, realistic scenario evaluations, and analysis of nonlinearity effects. The simulation results include the comparison of the proposed DO-PIDFFD2F and DO-PIDFF controllers with PIDF and PID controllers tuned using different metaheuristic algorithms from the literature. The obtained results show that the proposed DO-PIDFFD2F control technique is highly successful in terms of stability and robustness. In conclusion, this study provides comprehensive and robust results supporting the effectiveness and superiority of the DO-PIDFFD2F control method on the FES system.

Description

Şahin, Ali Kıvanç/0000-0003-4539-6419;

Keywords

FES System, PIDFFD2F Controller, PIDFF Controller, Do

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Q2

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Biomedical Signal Processing and Control

Volume

103

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