Multi-strategy modified INFO algorithm: Performance analysis and application to functional electrical stimulation system


İZCİ D., EKİNCİ S., Eker E., Demiro A.

JOURNAL OF COMPUTATIONAL SCIENCE, vol.64, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 64
  • Publication Date: 2022
  • Doi Number: 10.1016/j.jocs.2022.101836
  • Journal Name: JOURNAL OF COMPUTATIONAL SCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Keywords: Weighted mean of vectors algorithm, Modified opposition -based learning, Le vy flight, Nelder-Mead method, Functional electrical stimulation, PID-F controller design, SIMPLEX-METHOD
  • Istanbul Technical University Affiliated: Yes

Abstract

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 liter-ature 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 Le ' vy 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 function is also proposed. The excellent ability of the developed m-INFO algorithm-based PID-F controller for FES system is demonstrated through comparative statistical, transient response and frequency response analyses using original weighted mean of vectors, marine predators and moth-flame optimization algorithms based PID-F controlled FES systems.