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Invited Speakers

 

Invited Speakers will be announced soon.

 

 

 

 

 

Previous Invited Speakers


Prof. Toufik Bakir
University of Burgundy, France

Toufik Bakir received his Ph.D. degree in industrial automatics from the University of Claude Bernard-Lyon I, Lyon, France, in 2006. He was an associate professor at the Le2i (Laboratory of electronics, computer science and image) at the University of Burgundy (2007-2020). He became a full professor since 2021 at ImViA (Image and Artificial Vision laboratory) of the University of Burgundy. He is the head of the computer science and electronics department since 2020. His research interests include dynamic systems, system modeling, optimization and control.

Speech Title: Functional Electrical Stimulation, from Modelling to Force Control
Abstract:
Recent functional electrical stimulation (FES) devices tend to use closed-loop control strategies to control the force and/or the fatigue levels by tuning parameters such as frequency, amplitude or pulse width of the stimulation signal. In this talk, we will present two ways to perform such control; the first one is based on physical model (Ding et al. model) and the second one is based on empirical model (locally valid model). In the case of Ding et al. model, we performed an experimental study to upgrade the model by including the effect of the stimulation amplitude on the developed force level. The modified version of the Ding et al. model is then used to estimate the unmeasured state variables (which describe the system dynamics) in order to control the force level using different strategies (nonlinear input output linearization, model predictive control, sliding mode, etc.). In the case of empirical model, a local model is generated using different ways (output filtering, model identification) in order to control the force level using P, PI or PID controller (combined with sliding mode strategy or optimized using some heuristics). These different strategies are compared in terms of calculation time and precision to define the most adapted one for real time implementation.