Direct Model-Reference Adaptive Control for Wheelchair Simulator Control via a Haptic Interface

Abstract

A wheelchair locomotion simulator (WCS) is an innovative solution to assess the biomechanical cost of wheelchairs (WC) accessibility in a controlled and safe virtual environment. In this context, this paper presents a haptic feedback control architecture based on a direct model reference adaptive control (MRAC) with intelligent tuning of its adaptation gains. The control objective is to follow the reference model velocity while producing the force feedback during the push phase, in order to faithfully recreate the dynamic behavior of the WC in a virtual environment. To accomplish this, a wheelchair ergometer model with friction is used to provide realistic navigation in the virtual environment (VE), by detecting and driving the wheelchair wheels. A two-wheeled vehicle model including the rolling resistance aspect is used to describe the wheelchair dynamic behavior. Since the controller adaptation gains are operated on the tracking error between the reference model and the simulator output, the WC model is also used as a reference model to specify the desired dynamics of the adaptive control system. For an optimal solution, an intelligent metaheuristic algorithm Elephant Herding Optimization (EHO) is employed to optimize the controller gain adaptation parameter to keep the tracking error as small as possible. Finally, the simulation results obtained show the effectiveness of the proposed control strategy.