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In spite of the presence of powered wheelchairs, some of the users still experience steering challenges and manoeuvring difficulties that limit their capacity of navigating effectively. For such users, steering support and assistive systems may be very necessary. To appreciate the assistance, there is need that the assistive control is adaptable to the user's steering behaviour. This paper contributes to wheelchair steering improvement by modelling the steering behaviour of powered wheelchair users, for integration into the control system. More precisely, the modelling is based on the improved Directed Potential Field (DPF) method for trajectory planning. The method has facilitated the formulation of a simple behaviour model that is also linear in parameters. To obtain the steering data for parameter identification, seven individuals participated in driving the wheelchair in different virtual worlds on the augmented platform. The obtained data facilitated the estimation of user parameters, using the ordinary least square method, with satisfactory regression analysis results.

Wheelchairs are broadly accepted and are widespread because of the assistance they provide to people with limited mobility. The design of a good controller generally involves the formulation of a comprehensive wheelchair model. Most dynamic models in the literature presume non-inclined planer surfaces within-doors, and therefore fail to take the combined effects of both gravitational forces and rolling friction on the usable-traction into consideration. Wheel-slip situations are also commonly neglected. This paper contributes to wheelchair modeling by proposing and formulating a dynamic model that considers the effects of rolling friction and gravitational potential on the wheelchair’s road-load force, on both inclined and non-inclined surfaces. The dynamic model is derived through the Euler Lagrange procedure, and wheel slip is determined by an approach that reduces the convectional number of slip-detection encoders. In the closed-loop model, the input-output feedback controller is proposed for tracking the user inputs by torque compensation. The optimality of the resulting minimum-phase closed-loop system is then ensured through the performance index of the non-linear continuous-time generalized predictive control with good simulation results.