Adaptive Motion Control of Nonholonomic Intelligent Walker-Human Systems

This paper focuses on motion control of active intelligent walkers robust to system parameter variations and uncertainties. It presents a new realistic control-oriented model and, based on this model, an adaptive motion control design to generate appropriate torques to keep the i-walker in front of the user at the desired distance. Our control design utilizes inverse kinematics equations derived from a two-body kinematic model and to adaptively generate the reference velocities for maintaining ideal relative position of i-walker with respect to the user. The torques to track the reference velocities are generated using an adaptive proportional-integral-derivative control scheme, which is robust to unknown torque disturbances, combined with a computed torque based feedback linearization unit and a high gain observer to estimate the wheel velocities. The designed control scheme is formally analyzed and simulation tested for both symmetric and asymmetric gait patterns.