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๐Ÿ” marko kostic ๐Ÿ“‚ Engineering
Showing 2459 results for "marko kostic" in Engineering
Engineering Preprint PDF DOI

Sequential Inference for Gaussian Processes: A Signal Processing Perspective

Daniel Waxman, Fernando Llorente, Petar M. Djuric ยท 2026

The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support theโ€ฆ

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Intelligent Self-tuning Active EMI Filtering for Electrified Automotive Power Systems Using Reinforcement Learning

Mahuizi Lu, Kelin Jia, Rajib Goswami, Yukun Hu ยท 2026

The rapid electrification and intelligence of modern transportation systems place stringent demands on the electromagnetic compatibility, reliability, and adaptability of automotive power electronics.โ€ฆ

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Engineering Preprint PDF DOI

LiDAR-based Dynamic Blockage Prediction: A Data-driven Approach for Learning Interactive Bayesian Models

Saleemullah Memon, Ali Krayani, Pamela Zontone, Lucio Marcenaro, David Martin Gomez, Carlo Regazzoni ยท 2026

Vehicular sensing-based intelligence has made substantial progress in transportation systems, leading to higher levels of safety and sustainability for smart cities and autonomous systems. This paper โ€ฆ

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Engineering Preprint PDF DOI

Feedback Linearization of Hyperbolic PDEs with Volterra Nonlinearities

Miroslav Krstic ยท 2026

Alberto Isidori's framework of geometric nonlinear control, and particularly of feedback linearization, is the inspiration behind PDE backstepping: apply a transfromation of the state to cast the planโ€ฆ

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Engineering Preprint PDF DOI

PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learning

Yassine Ibork, Nhat Ha Nguyen, Myounggyu Won, Lokesh Das ยท 2026

We present a priority-aware intelligent lane change advisory system based on multi-agent federated reinforcement learning, namely PALCAS, for autonomous vehicles (AVs). While existing lane-change apprโ€ฆ

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Engineering Preprint PDF DOI

Learning to Route Electric Trucks Under Operational Uncertainty

Stavros Orfanoudakis, Ziyan Li, Ruixiao Yang, Nikolay Aristov, Pedro P. Vergara, Chuchu Fan, Elenna Dugundji ยท 2026

Electric truck operations require routing decisions that remain feasible under limited battery range, long charging times, travel and energy consumption, and competition for shared charging infrastrucโ€ฆ

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Engineering Preprint PDF DOI

Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems

Junya Ikemoto, Satoshi Maruyama, Kazumune Hashimoto ยท 2026

This paper proposes a deep reinforcement learning (DRL)-based event-triggered controller design for networked artificial pancreas (AP) systems. Although existing DRL-based AP controllers typically assโ€ฆ

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Engineering Preprint PDF DOI

Optimal-Control Suggestion for Congestion on Freeways using Data Assimilation of Distributed Fiber-Optic Sensing

Yoshiyuki Yajima, Hemant Prasad, Daisuke Ikefuji, Takemasa Suzuki, Shin Tominaga, Hitoshi Sakurai, Manabu Otani ยท 2026

This paper presents the optimal-control suggestion for congestion on freeways using data assimilation (DA) of distributed fiber-optic sensing (DFOS). To simultaneously maximize throughput and avoid/miโ€ฆ

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Engineering Preprint PDF DOI

Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

Sakiko Mishima, Yoshiyuki Yajima, Noriyuki Tonami, Tomoyuki Hino, Shugo Aibe, Junichiro Saikawa, Koji Mizuguchi ยท 2026

This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic Sensing (DAS), which is one of the distributed fibโ€ฆ

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Engineering Preprint PDF DOI

Data-Driven Privacy-Preserving Modeling and Frequency Regulation with Aggregated Electric Vehicles via Bilinear Hidden Markov Model

Yiping Liu, Xiaozhe Wang, Geza Joos ยท 2026

Vehicle-to-Grid (V2G) technology allows bidirectional power flow for real-time grid support, making electric vehicles (EVs) well-suited for ancillary services such as frequency regulation. However, exโ€ฆ

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Engineering Preprint PDF DOI

Agent-Centric Visual Reinforcement Learning under Dynamic Perturbations

Zhengru Fang, Yu Guo, Fei Liu, Yuang Zhang, Yihang Tao, Senkang Hu, Wenbo Ding, Yuguang Fang ยท 2026

Visual reinforcement learning aims to empower an agent to learn policies from visual observations, yet it remains vulnerable to dynamic visual perturbations, such as unpredictable shifts in corruptionโ€ฆ

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Engineering Preprint PDF DOI

AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation

Kai Yang, Zedong Chu, Yingnan Guo, Zhengbo Wang, Shichao Xie, Yanfen Shen, Xiaolong Wu, Xing Li, Mu Xu ยท 2026

While Vision-Language-Action (VLA) models have been demonstrated possessing strong zero-shot generalization for robot control, their massive parameter sizes typically necessitate cloud-based deploymenโ€ฆ

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Engineering Preprint PDF DOI

Private and Common Information States in Decentralized Parallel Dynamic Programming for Delayed Sharing Patterns

Charalambos D. Charalambous, Umarbek Guvercin, Seddik Djouadi ยท 2026

This paper develops a dynamic programming (DP) approach for decentralized stochastic optimal control problems with delayed sharing information patterns, which exhibits the fundamental Properties of clโ€ฆ

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Probabilistic Hazard Analysis Framework with Stochastic Optimal Control for Deteriorating Civil Infrastructure Systems

Sudhir P. Jodha, Konstantinos G. Papakonstantinou ยท 2026

The safety and resilience of civil infrastructure systems are increasingly threatened by compounded risks from various hazard events and structural deterioration due to environmental stressors. This sโ€ฆ

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Engineering Preprint PDF DOI

ATRS: Adaptive Trajectory Re-splitting via a Shared Neural Policy for Parallel Optimization

Jiajun Yu, Guodong Liu, Li Wang, Pengxiang Zhou, Wentao Liu, Yin He, Chao Xu, Fei Gao, Yanjun Cao ยท 2026

Parallel trajectory optimization via the Alternating Direction Method of Multipliers (ADMM) has emerged as a scalable approach to long-horizon motion planning. However, existing frameworks typically dโ€ฆ

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Engineering Preprint PDF DOI

Mobility Aware Power Control for VCSEL Based Indoor OWC

Walter Zibusiso Ncube, Ahmad Adnan Qidan, Taisir El-Gorashi, Jaafar M. H. Elmirghani ยท 2026

Optical wireless communication (OWC) is a promising technology for supporting data intensive services in indoor environments due to its large unregulated spectrum, high spatial reuse, and potential foโ€ฆ

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Engineering Preprint PDF DOI

A Hidden Markov Framework for Physically Interpretable Arc Stability Dynamics in Welding Systems

Hidir Selcuk Nogay ยท 2026

Electric arc welding (EAW) exhibits strongly non stationary and temporally evolving behavior, making reliable assessment of arc stability difficult using conventional frame based approaches. In this sโ€ฆ

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Engineering Preprint PDF DOI

SLAM as a Stochastic Control Problem with Partial Information: Optimal Solutions and Rigorous Approximations

Ilir Gusija, Fady Alajaji, Serdar Yuksel ยท 2026

Simultaneous localization and mapping (SLAM) is a foundational state estimation problem in robotics in which a robot accurately constructs a map of its environment while also localizing itself within โ€ฆ

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Engineering Preprint PDF DOI

Self-Predictive Representation for Autonomous UAV Object-Goal Navigation

Angel Ayala, Donling Sui, Francisco Cruz, Mitchell Torok, Mohammad Deghat, Bruno J. T. Fernandes ยท 2026

Autonomous Unmanned Aerial Vehicles (UAVs) have revolutionized industries through their versatility with applications including aerial surveillance, search and rescue, agriculture, and delivery. Theirโ€ฆ

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Engineering Preprint PDF DOI

Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly

Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Matteo Leonetti, Emmanouil Spyrakos-Papastavridis, Shan Luo ยท 2026

Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling such tasks, it requires extensive exploration. Inโ€ฆ

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