Nonlinear model predictive control of functional electrical stimulation. (January 2017)

• Record Type: Journal Article
• Authors: Kirsch, Nicholas; Alibeji, Naji; Sharma, Nitin
• Is Part Of: Control engineering practice. Volume 58(2017)
• Page Start: 319
• Page End: 331
• Publication Date: 2017-01
• Subjects: Functional electrical stimulation -- Nonlinear model predictive control -- Muscle parameter identification -- Rehabilitation engineering -- Gradient projection algorithm; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2016.03.005
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Minimizing the amount of electrical stimulation can potentially mitigate the adverse effects of muscle fatigue during functional electrical stimulation (FES) induced limb movements. A gradient projection-based model predictive controller is presented for optimal control of a knee extension elicited via FES. A control Lyapunov function was used as a terminal cost to ensure stability of the model predictive control. The controller validation results show that the algorithm can be implemented in real-time with a steady-state RMS error of less than 2°. The experiments also show that the controller follows step changes in desired angles and is robust to external disturbances.