Related papers: Robust Commutation Design: Applied to Switched Rel…
Having simultaneously a high quality factor (i.e. a narrow resonant band) and a shorter interaction time between the resonating system and the external sources (i.e. a wide resonant band) is a desirable characteristic for mechanical…
As an unconventional magnet, altermagnetism attracts great interest in condensed matter physics and applies a new research platform for the spintronics. Since the tunneling magnetoresistance (TMR) effect is an important research aspect in…
This contributions discusses the simulation of magnetothermal effects in superconducting magnets as used in particle accelerators. An iterative coupling scheme using reduced order models between a magnetothermal partial differential model…
The intrinsic modularity and reconfigurability of modular reconfigurable robots (MRR) confer advantages such as versatility, fault tolerance, and economic efficacy, thereby showcasing considerable potential across diverse applications. The…
Electrical manipulation of spin textures inside antiferromagnets represents a new opportunity for developing spintronics with superior speed and high device density. Injecting spin currents into antiferromagnets and realizing efficient…
Being able to effectively locate saddle (and other fixed) points in dynamical systems holds tremendous implications in a number of applications in engineering and science, among which the study of rare events in molecular simulations stands…
Robot manipulators have become a significant tool for production industries due to their advantages in high speed, accuracy, safety, and repeatability. This paper simulates and optimizes the design of a 3-DOF articulated robotic manipulator…
The performance of model predictive controllers (MPC) strongly depends on the model quality. In the field of electric drive control, white-box (WB) modeling approaches derived from first-order physical principles are most common. This…
Reinforcement learning (RL) has emerged as an effective post-training paradigm for enhancing the reasoning capabilities of multimodal large language model (MLLM). However, current RL pipelines often suffer from training inefficiencies…
Symbolic control problems aim to synthesize control policies for dynamical systems under complex temporal specifications. For such problems, Signal Temporal Logic (STL) is increasingly used as the formal specification language due to its…
We report the possibility of achieving an order of magnitude reduction in the energy dissipation needed to write bits in perpendicular magnetic tunnel junctions (p-MTJs) by simulating the magnetization dynamics under a combination of…
Magnetic materials with strong perpendicular magnetic anisotropy are of great interest for the development of nonvolatile magnetic memory and computing technologies due to their high stabilities at the nanoscale. However, electrical…
Sampling-based motion planning has emerged as a powerful approach for robotics, enabling exploration of complex, high-dimensional configuration spaces. When combined with Signal Temporal Logic (STL), a temporal logic widely used for…
The increasing need for sharing workspace and interactive physical tasks between robots and humans has raised concerns regarding safety of such operations. In this regard, controllable clutches have shown great potential for addressing…
Modular Aerial Robot Systems (MARS) consist of multiple drone modules that are physically bound together to form a single structure for flight. Exploiting structural redundancy, MARS can be reconfigured into different formations to mitigate…
The Vehicle Routing Problem (VRP) is the combinatorial optimization problem of designing routes for vehicles to visit customers in such a fashion that a cost function, typically the number of vehicles, or the total travelled distance is…
This paper proposes a robust control of doublefed induction generator of wind turbine to optimize its production: that means the energy quality and efficiency. The proposed control reposes in the sliding mode control using a multimodel…
This study addresses a gap in the utilization of Reinforcement Learning (RL) and Machine Learning (ML) techniques in solving the Stochastic Vehicle Routing Problem (SVRP) that involves the challenging task of optimizing vehicle routes under…
In this work, an advanced motion controller is proposed for buck converter-fed DC motor systems. The design is based on an idea of active disturbance rejection control (ADRC) with its key component being a custom observer capable of…
To increase the efficiency of future electric vehicles, it is crucial to reduce drivetrain losses in battery-powered vehicles. This enables either an increase in driving range or overall cost savings by reducing battery capacity while…