Related papers: Active Compensation of Position Dependent Flexible…
Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion…
This paper outlines a complete methodology for modeling an on-orbit servicing mission scenario and designing a feedback control system for the attitude dynamics that is guaranteed to robustly meet pointing requirements, despite model…
Automated vehicles and logistics robots must often position themselves in narrow environments with high precision in front of a specific target, such as a package or their charging station. Often, these docking scenarios are solved in two…
Curve and surface fairing is crucial in computer-aided geometric design, influencing product quality, physical performance, and aesthetics. Traditional methods often apply global modifications, lacking fine-grained control. This paper…
Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achieving precise manipulation while maintaining coordinated locomotion remains a major…
Sensory substitution is an effective approach for displaying stable haptic feedback to a teleoperator under time delay. The finger is highly articulated, and can sense movement and force in many directions, making it a promising location…
In contemporary control theory, self-adaptive methodologies are highly esteemed for their inherent flexibility and robustness in managing modeling uncertainties. Particularly, robust adaptive control stands out owing to its potent…
The development of efficient and robust dynamic models is fundamental in the field of systems and control engineering. In this paper, a new formulation for the dynamic model of nonlinear mechanical systems, that can be applied to different…
It is always a challenging task for multi-agent systems to achieve efficient and robust coverage in uncertain environments. The absence of global positioning information on the uncertain environment introduces significant complexity to the…
Adaptive control is a critical component of reliable robot autonomy in rapidly changing operational conditions. Adaptive control designs benefit from a disturbance model, which is often unavailable in practice. This motivates the use of…
The growing penetration of renewable energy requires upgrades to the transmission network to ensure the deliverability of renewable generation. As an efficient alternative to transmission expansion, flexible transmission technologies, whose…
Current developments of high-speed magnetic levitation technology using the principle of the electromagnet suspension (EMS) focus on reaching vehicle speeds of more than 600 km/h. With increasing vehicle speeds, however, updated control…
Position sensitive detectors (PSDs) offer possibility to track single active marker's two (or three) degrees of freedom (DoF) position with a high accuracy, while having a fast response time with high update frequency and low latency, all…
A key ingredient to achieving intelligent behavior is physical understanding that equips robots with the ability to reason about the effects of their actions in a dynamic environment. Several methods have been proposed to learn dynamics…
Predictive Stator Current Control (PSCC) has been proposed for control of multi-phase drives. The flexibility offered by the use of a Cost Function has been used to deal with the increased number of phases. However, tuning of the Weighting…
As global battery demand increases, real-time process control becomes increasingly important for battery electrode manufacturing, yet slot-die lines are still mostly manually operated in open loop. This paper develops a physics-based…
This is the first part of four series papers, aiming at the problem of actuator dynamics compensation for linear systems. We consider the stabilization of a type of cascade abstract linear systems which model the actuator dynamics…
This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models and safety guarantees. As machine learning techniques…
Handling objects with unknown or changing masses is a common challenge in robotics, often leading to errors or instability if the control system cannot adapt in real-time. In this paper, we present a novel approach that enables a…
When intelligent spacecraft or space robots perform tasks in a complex environment, the controllable variables are usually not directly available and have to be inferred from high-dimensional observable variables, such as outputs of neural…