Parametrised Function ILC with application to FES Electrode Arrays

Functional electrical stimulation (FES) is an effective approach to regain lost movement in paralysed or impaired subjects. FES arrays can achieve functional multi-joint angular motion by activating a large number of FES elements. However, their control is challenging due to the need for high precision but the lack of a model or available identification time in a clinical or home setting. This paper develops an approach to deliver high accuracy with minimal identification overhead. It is based on iterative learning control (ILC), a technique that exploits the repeated nature of rehabilitation training. It uses a parameterised model form that adapts to new data and replaces identification tests while maintaining accuracy. Results show that 4 references can be tracked using only 10.8% of the experimental tests required by conventional ILC approaches.

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