Adaptive intelligent assistance control of electrical wheelchairs by grey-fuzzy decision-making algorithm

Many potential accidents due to direct control of electrical wheelchair may be occurred by unreasonable control in various internal or external environmental conditions, such as the uncertainties of the front caster wheels and the unbalanced friction condition between wheels and floor. This paper presents a grey-fuzzy decision-making (GFD) algorithm based on grey prediction theory and fuzzy logic theory. The GFD is able to estimate optimal parameters approximating to the real system dynamics mode according to the observed information. The application of intelligent assistant control of an electrical wheelchair investigated. We conduct the experiments by multisensor based wheelchairs "Luoson#1" and "Luoson#3". The GFD controller is presented to integrate the electronic compass and dead reckoning measurements for the reduction of the influence caused by the uncertainties. The results have demonstrated the system capability for the increased certainty and safety to operate the electrical wheelchairs.