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Adaptive backstepping controller with Kalman state estimator for stabilisation and manoeuvre of pedestrian controlled uniaxial transport vehicles

: Brüning, M.; Thiele, Gregor; Schönewolf, W.; Krüger, J.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Industrial Electronics Society -IES-:
IEEE International Conference on Mechatronics, ICM 2015 : Nagoya, Japan, 6 - 8 March 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4799-3633-5
ISBN: 978-1-4799-3634-2
International Conference on Mechatronics (ICM) <2015, Nagoya>
Conference Paper
Fraunhofer IPK ()

Pedestrian controlled uniaxial vehicles for goods transport such as hand trucks offer intuitive manoeuvrability with little space requirements. The disadvantage of this class of statically underdetermined vehicles is the need for the user to apply force for both stabilisation and propulsion. Removing this disadvantage is the key to enable their use for convenient transportation of heavy goods over long distances. For this our solution approach is to equip the vehicle with controlled drives providing force for both balancing and propulsion. Different to uniaxial vehicles without payload or for passenger transportation controller's adaptation to kinematic and dynamic parameters is required here after every reload. The frame's pitch angle must be adapted with every change of load whereby the COG's position is not measurable with acceptable effort. Dynamic parameters vary in a wide range. We applied an adaptive controller based on backstepping combined with Kalman state estimation for stable balancing with adaptation to changed payload without need for external support from the user. The manoeuvre concept based on low interaction forces applied from the user to the vehicle frame is taking advantage of the underconstrained dynamics of the vehicle, and offers similar driving behaviour to the user with different load situations. Operating control levers for setting speed is not required. To allow for cheap production a design goal was not requiring sensor information of both load's absolute weight and user interaction forces. The adaptive control and state estimation concept was simulated based on the kinematic and dynamic model of our new uniaxial vehicle system designed for urban parcel distribution on foot. Simulation results show the correct operation of the approach.