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In this paper, we present a novel developmental reinforcement learning-based controller for a quadcopter with thrust vectoring capabilities. This multirotor UAV design has tilt-enabled rotors. It utilizes the rotor force magnitude and…

Robotics · Computer Science 2020-07-16 Aditya M. Deshpande , Rumit Kumar , Ali A. Minai , Manish Kumar

The Modboat is an autonomous surface robot that turns the oscillation of a single motor into a controlled paddling motion through passive flippers. Inertial control methods developed in prior work can successfully drive the Modboat along…

Robotics · Computer Science 2022-02-04 Gedaliah Knizhnik , Mark Yim

Control theory provides engineers with a multitude of tools to design controllers that manipulate the closed-loop behavior and stability of dynamical systems. These methods rely heavily on insights about the mathematical model governing the…

Systems and Control · Electrical Eng. & Systems 2020-09-24 Simen Theie Havenstrøm , Camilla Sterud , Adil Rasheed , Omer San

Safe flight in dynamic environments requires unmanned aerial vehicles (UAVs) to make effective decisions when navigating cluttered spaces with moving obstacles. Traditional approaches often decompose decision-making into hierarchical…

Robotics · Computer Science 2025-02-25 Zhefan Xu , Xinming Han , Haoyu Shen , Hanyu Jin , Kenji Shimada

Autonomous aerial systems play an increasingly vital role in a wide range of applications, particularly for transport and delivery tasks in complex environments. In airdrop missions, these platforms face the dual challenges of abrupt…

Robotics · Computer Science 2025-07-21 Ziliang Li , Hongming Chen , Yiyang Lin , Biyu Ye , Ximin Lyu

Airborne Wind Energy is a lightweight technology that allows power extraction from the wind using airborne devices such as kites and gliders, where the airfoil orientation can be dynamically controlled in order to maximize performance. The…

Fluid Dynamics · Physics 2022-03-29 N. Orzan , C. Leone , A. Mazzolini , J. Oyero , A. Celani

This paper investigates the use of Reinforcement Learning for the robust design of low-thrust interplanetary trajectories in presence of severe disturbances, modeled alternatively as Gaussian additive process noise, observation noise,…

Machine Learning · Computer Science 2020-08-20 Alessandro Zavoli , Lorenzo Federici

Designing missiles' autopilot controllers has been a complex task, given the extensive flight envelope and the nonlinear flight dynamics. A solution that can excel both in nominal performance and in robustness to uncertainties is still to…

Machine Learning · Computer Science 2021-09-21 Bernardo Cortez

This paper presents a method to control a manipulator system grasping a rigid-body payload so that the motion of the combined system in consequence of externally applied forces to be the same as another free-floating rigid-body (with…

Robotics · Computer Science 2022-09-20 Farhad Aghili

Nowadays, liquid rocket engines use closed-loop control at most near steady operating conditions. The control of the transient phases is traditionally performed in open-loop due to highly nonlinear system dynamics. This situation is…

Machine Learning · Computer Science 2021-05-27 Günther Waxenegger-Wilfing , Kai Dresia , Jan Christian Deeken , Michael Oschwald

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing…

Artificial Intelligence · Computer Science 2024-07-02 Luis E. Alvarez , Marc W. Brittain , Steven D. Young

This paper presents the results of a new deep learning model for traffic signal control. In this model, a novel state space approach is proposed to capture the main attributes of the control environment and the underlying temporal traffic…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Matthew Muresan , Liping Fu , Guangyuan Pan

Recently, there has been a surge in interest in safe and robust techniques within reinforcement learning (RL). Current notions of risk in RL fail to capture the potential for systemic failures such as abrupt stoppages from system failures…

Systems and Control · Computer Science 2019-10-09 David Mguni

Autonomous Rendezvous and Docking (RVD) have been extensively studied in recent years, addressing the stringent requirements of spacecraft dynamics variations and the limitations of GNC systems. This paper presents an innovative approach…

Machine Learning · Computer Science 2024-10-22 Matteo Stoisa , Federica Paganelli Azza , Luca Romanelli , Mattia Varile

Turbulent-flow control aims to develop strategies that effectively manipulate fluid systems, such as the reduction of drag in transportation and enhancing energy efficiency, both critical steps towards reducing global CO$_2$ emissions. Deep…

Fluid Dynamics · Physics 2026-05-25 Miguel Beneitez , Andres Cremades , Luca Guastoni , Ricardo Vinuesa

This paper focuses on the spacecraft attitude control problem with intermittent actuator activation, taking into account the attitude rotation rate limitation and input saturation issue simultaneously. To address this problem, we first…

Systems and Control · Electrical Eng. & Systems 2023-06-01 Jiakun Lei , Tao Meng , Kun Wang , Weijia Wang , Shujian Sun

With the growing demands for Autonomous Surface Vehicles (ASVs) in recent years, the number of ASVs being deployed for various maritime missions is expected to increase rapidly in the near future. However, it is still challenging for ASVs…

Robotics · Computer Science 2024-12-13 Xi Lin , Paul Szenher , Yewei Huang , Brendan Englot

We study the control of transport properties in a deterministic inertia ratchet system via the extended delay feedback method. A chaotic current of a deterministic inertia ratchet system is controlled to a regular current by stabilizing…

Chaotic Dynamics · Physics 2007-05-23 Woo-Sik Son , Jung-Wan Ryu , Dong-Uk Hwang , Soo-Young Lee , Young-Jai Park , Chil-Min Kim

Repetitive operations are widely conducted by automatic machines in industry. Periodic disturbances induced by the repetitive operations must be compensated to achieve precise functioning. In this paper, a periodic-disturbance observer…

Systems and Control · Electrical Eng. & Systems 2022-07-05 Hisayoshi Muramatsu , Seiichiro Katsura

In this work, we investigate the problem of simultaneously learning and controlling a system subject to adversarial choices of disturbances and system parameters. We study the problem for a scalar system with $l_\infty$-norm bounded…

Optimization and Control · Mathematics 2018-12-31 Dimitar Ho , Nikolai Matni , John C. Doyle
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