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Multi-strategy modified INFO algorithm: Performance analysis and application to functional electrical stimulation system by Davut Izci; Serdar Ekinci; Erdal Eker; Ayşen Demirören is a Computer Science article available to read on EtoBox.

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A functional electrical stimulation (FES) system holds a significant importance for the paralyzed individuals as it can help them to perform the tasks they are unable to do. It is crucial to develop an efficient control mechanism for the FES system as it acts on the human musculoskeletal system which presents noise and uncertainties. Therefore, this paper proposes a novel control method for efficient operation of the FES system. In this regard, a proportional-integral-derivative controller with filter (PID-F) mechanism is proposed for the first time in literature for efficient operation of the FES system. Besides, a novel multi-strategy based weighted mean of vectors algorithm (m-INFO) is also developed using a modified opposition-based learning and Lévy flight mechanism together with Nelder-Mead simplex search method. Unimodal, multimodal, low-dimensional and CEC2019 benchmark functions are used to demonstrate the excellent performance of the proposed m-INFO algorithm against several other metaheuristic optimizers. The proposed m-INFO algorithm is then used as an efficient tool to design the PID-F controlled FES system. To achieve optimal tuning, a simple yet effective objective f

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Author

Davut Izci; Serdar Ekinci; Erdal Eker; Ayşen Demirören

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Computer Science (Physical Sciences)