Figure 1. We developed and applied the Adaptive Super Twisting Controller method both to cable-driven parallel robots (left) and to UAVs (right).
During my time at the Max Planck Institute for Biological Cybernetics I worked on the application of sliding mode controllers, and particularly of the Adaptive Super Twisting Controller from Shtessel et al. (2012), both to cable-driven parallel robots and UAVs. What is remarkable about this method is that:
it considers all the uncertainties (parametric, model,disturbances) lumped together;
it does not require the knowledge of the upper bound ofthe uncertainties;
rather than adapting the parameters of the model, it adapts the gains;
it uses a feedforward dynamic inversion (FF) to reduce the discontinuous control, thus improving performance and further reducing chattering.
Figure 2. Results from the application of an Adaptive Super Twisting controller to an UAV. The plots show that the controller is able to quickly react to unforeseen external disturbances.
Related Publications
2018
Conference
Application of a Differentiator-Based Adaptive Super-Twisting Controller for a Redundant Cable-Driven Parallel Robot
C. Schenk, C. Masone, A. Pott, and Heinrich H. Bülthoff
In this paper we present preliminary, experimental results of an Adaptive Super-Twisting Sliding-Mode Controller with time-varying gains for redundant Cable-Driven Parallel Robots. The sliding-mode controller is paired with a feed-forward action based on dynamics inversion. An exact sliding-mode differentiator is implemented to retrieve the velocity of the end-effector using only encoder measurements with the properties of finite-time convergence, robustness against perturbations and noise filtering. The platform used to validate the controller is a robot with eight cables and six degrees of freedom powered by 940W compact servo drives. The proposed experiment demonstrates the performance of the controller, finite-time convergence and robustness in tracking a trajectory while subject to external disturbances up to approximately 400% the mass of the end-effector.
@inproceedings{Schenk-2018-supertwisting,author={Schenk, C. and Masone, C. and Pott, A. and Bülthoff, Heinrich H.},editor={Gosselin, C. and Cardou, P. and Bruckmann, T. and Pott, A.},title={Application of a Differentiator-Based Adaptive Super-Twisting Controller for a Redundant Cable-Driven Parallel Robot},booktitle={Cable-Driven Parallel Robots},year={2018},publisher={Springer International Publishing},address={Cham},pages={254-267},doi={10.1007/978-3-319-61431-1_22},keywords={cable robot,robust control, CableRobot simulator},}
2016
Conference
Adaptive Super Twisting Controller for a quadrotor UAV
S. Rajappa, C. Masone, H. H. Bülthoff, and P. Stegagno
In IEEE International Conference on Robotics and Automation (ICRA), 2016
In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.
@inproceedings{Rajappa-2016-supertwisting,author={Rajappa, S. and Masone, C. and Bülthoff, H. H. and Stegagno, P.},booktitle={IEEE International Conference on Robotics and Automation (ICRA)},title={Adaptive Super Twisting Controller for a quadrotor {UAV}},year={2016},volume={},number={},pages={2971-2977},doi={10.1109/ICRA.2016.7487462},keywords={robust control, aerial robotics},}
