This paper describes the implementation of a neural network control system for guiding a wheelchair, using an architecture based on a digital signal processor (DSP). The control algorithm is based on a radial base network model, the main advantage of which is learning speed. The hub of the algorithm architecture is a DSP of the company Texas Instruments (TMS320C31). The board has complete autonomy of action and is specially designed for executing control algorithms in real time. The wheelchair prototype forms part of the SIAMO project, currently being developed by the Electronics Department of the University of Alcala. The stability conditions are obtained for the correct functioning of the system and variour simulations are conducted to deduce the correct functioning of the system when govering the output of the wheelchair.
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