Observer-Based Assistive Control Design Under Time-Varying Sampling for Power-Assisted Wheelchairs

Abstract Compared to manual wheelchairs and fully electric powered wheelchairs, power-assisted wheelchairs (PAWs) provide a special structure where the human can use her/his propulsion to interact with the assistive system. In this context, different studies have focused on the assistive control of PAWs in recent years. This paper presents an observed-based assistive control design using only position encoders. With a time-varying sampling induced by these position encoders, the wheelchair is described by a discrete-time Linear Parameter Varying model. Based on a Takagi-Sugeno (TS) representation, an observer is designed by using LMI techniques. According to the estimated human torques, we use the frequencies with which the wheels are pushed to compute the reference velocity of the centre of gravity. The wheelchair turns with a constant yaw velocity when one of two wheels is braked by the human. Reference tracking is accomplished by a PI controller. Simulation results confirm that the proposed assistive control algorithm provides a good maneuverability for users to control the velocity of the centre of gravity and the yaw velocity of the wheelchair.