Related papers: Trend-Based SAC Beam Control Method with Zero-Shot…
Large energy acceptance arcs have been proposed for applications such as cancer therapy, muon accelerators, and recirculating linacs. The efficacy of charged particle therapy can be improved by reducing the energy layer switching time,…
The shift toward sixth-generation (6G) wireless networks places integrated sensing and communications (ISAC) at the core of future applications such as autonomous driving, extended reality, and smart manufacturing. However, the combination…
The uncertainty of the sensing target brings great challenge to the beamforming design of the integrated sensing and communication (ISAC) system. To address this issue, we model the scattering coefficient and azimuth angle of the target as…
Terahertz (THz) integrated sensing and communication (ISAC) enables simultaneous data transmission with Terabit-per-second (Tbps) rate and millimeter-level accurate sensing. To realize such a blueprint, ultra-massive antenna arrays with…
Multimodal Diffusion Transformers (MM-DiTs) have achieved remarkable progress in text-driven visual generation. However, even state-of-the-art MM-DiT models like FLUX struggle with achieving precise alignment between text prompts and…
In industrial systems, certain process variables that need to be monitored for detecting faults are often difficult or impossible to measure. Soft sensor techniques are widely used to estimate such difficult-to-measure process variables…
This paper presents the application of a novel data-driven adaptive control technique, called dynamic mode adaptive control (DMAC), for regulating thrust in a solid fuel ramjet (SFRJ). A high-fidelity computational model incorporating…
Superionic conductors, or solid-state ion-conductors surpassing 0.01 S/cm in conductivity, can enable more energy dense batteries, robust artificial ion pumps, and optimized fuel cells. However, tailoring superionic conductors require…
We propose a new method for the problem of controlling linear dynamical systems under partial observation and adversarial disturbances. Our new algorithm, Double Spectral Control (DSC), matches the best known regret guarantees while…
We consider a source that wishes to communicate with a destination at a desired rate, over a mmWave network where links are subject to blockage and nodes to failure (e.g., in a hostile military environment). To achieve resilience to link…
Fault-tolerant flight control faces challenges, as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited system complexity due to their low sample efficiency. In this…
As compared to electron storage rings, one advantage of recirculating linear accelerators is that the beam properties at target are no longer dominated by the equilibrium between quantum radiative diffusion and radiation damping because new…
This paper proposes a method for direct torque control of Brushless DC (BLDC) motors. Evaluating the trapezium of back-EMF is needed, and is done via a sliding mode observer employing just one measurement of stator current. The effect of…
Proximal Policy Optimization (PPO) has become the de facto standard for training legged robots, thanks to its robustness and scalability in massively parallel simulation environments like IsaacLab. However, its on-policy nature makes it…
It is nontrivial to achieve global zero-error regulation for uncertain nonlinear systems. The underlying problem becomes even more challenging if mismatched uncertainties and unknown time-varying control gain are involved, yet certain…
Actor-critic algorithms address the dual goals of reinforcement learning (RL), policy evaluation and improvement via two separate function approximators. The practicality of this approach comes at the expense of training instability, caused…
Arm end-effector stabilization is essential for humanoid loco-manipulation tasks, yet it remains challenging due to the high degrees of freedom and inherent dynamic instability of bipedal robot structures. Previous model-based controllers…
Actor-critic methods, a type of model-free Reinforcement Learning, have been successfully applied to challenging tasks in continuous control, often achieving state-of-the art performance. However, wide-scale adoption of these methods in…
We present a fast trajectory optimization algorithm for the soft capture of uncooperative tumbling space objects. Our algorithm generates safe, dynamically feasible, and minimum-fuel trajectories for a six-degree-of-freedom servicing…
While Soft Actor-Critic (SAC) is highly effective in continuous control, its discrete counterpart (DSAC) performs poorly on challenging discrete-action domains such as Atari. Consequently, starting from DSAC, we revisit the design of…