arXiv:2608. 06419v1 Announce Type: cross Abstract: In this paper, we address the certification of datadriven feedforward control for periodic tracking of unknown nonlinear systems under partial state measurements.
By Berk Altiner, Rajasree Sarkar, Arunava Banerjee, Zongxuan Sun, Kenneth Kim
This study explores temporal neural networks for estimating the end‑effector position of an aerial continuum manipulator (ACM) affected by aerodynamic disturbances from a UAV. An experimental dataset covering stationary and free‑hovering conditions across various robot configurations and altitudes was used to evaluate strain‑parameterized kinematic models and to benchmark a closed‑form continuous‑time (CfC) neural network against an MLP and a GRU. The CfC network achieved a 22 mm RMSE, outperforming the MLP (36 mm) and GRU (28 mm) by 39.5 % and 20.6 %, respectively, demonstrating the advantage of continuous‑time learning for this task.
By Niloufar Amiri, Houman Masnavi, Farrokh Janabi-Sharifi
arXiv:2606. 31199v1 Announce Type: cross Abstract: The control of agile quadrotors in dynamic and uncertain environments remains an open area of investigation to this day, particularly when the complete system dynamics are partially known or highly nonlinear.
By Amos Alwala, Gabriel da Silva Lima, Wallace Moreira Bessa
arXiv:2607. 10026v1 Announce Type: cross Abstract: This paper proposes a new notion of robust invertibility for nonlinear dynamical systems, and introduces constructive parameterizations of recurrent neural network which are robustly invertible by design.
By Yurui Zhang, Ruigang Wang, Ian R. Manchester
arXiv:2606. 08714v1 Announce Type: cross Abstract: Multirotors are widely used in applications ranging from surveillance to precision agriculture, yet conventional designs remain limited by their under-actuation.
By Ali Kafili Gavgani, Amin Talaeizadeh, Aria Alasty, Hossein Nejat Pishkenari
arXiv:2510. 21874v2 Announce Type: replace-cross Abstract: Unmanned aerial vehicles (UAVs) operating in dynamic wind fields must generate safe and energy-efficient trajectories under physical and environmental constraints.
By Shuning Zhang