Imagen de Portada

Feasible Pairings for Decentralized Integral Controllability of Non-Square Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tong, Yuhao, Su, Steven W.
Formato:	Preprint
Publicado:	2026
Materias:	Optimization and Control Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Sufficient D-Stability Conditions for Non-Square Matrices
por: Tong, Yuhao, et al.
Publicado: (2024)

Adaptive Online Non-stochastic Control
por: Mhaisen, Naram, et al.
Publicado: (2023)

Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputs
por: Li, Ming, et al.
Publicado: (2024)

Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments
por: Kara, Ali Devran, et al.
Publicado: (2023)

Approximate Information States for Worst-Case Control and Learning in Uncertain Systems
por: Dave, Aditya, et al.
Publicado: (2023)

Safe Decentralized Operation of EV Virtual Power Plant with Limited Network Visibility via Multi-Agent Reinforcement Learning
por: Huang, Chenghao, et al.
Publicado: (2026)

Agent-Based Decentralized Energy Management of EV Charging Station with Solar Photovoltaics via Multi-Agent Reinforcement Learning
por: Fan, Jiarong, et al.
Publicado: (2025)

A Lyapunov Characterization of Robust D-Stability with Application to Decentralized Integral Control of LTI Systems
por: Casasanta, John-Paolo, et al.
Publicado: (2026)

Towards Faster Decentralized Stochastic Optimization with Communication Compression
por: Islamov, Rustem, et al.
Publicado: (2024)

Wasserstein gradient flow for optimal probability measure decomposition
por: Han, Jiangze, et al.
Publicado: (2024)

Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations
por: Kungurtsev, Vyacheslav, et al.
Publicado: (2025)

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
por: Choudhury, Sayantan, et al.
Publicado: (2024)

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
por: Li, Siying, et al.
Publicado: (2025)

A Penalty-Based Guardrail Algorithm for Non-Decreasing Optimization with Inequality Constraints
por: Stepanovic, Ksenija, et al.
Publicado: (2024)

A Robust Algorithm for Non-IID Machine Learning Problems with Convergence Analysis
por: Xu, Qing, et al.
Publicado: (2025)

Unsupervised Training of Diffusion Models for Feasible Solution Generation in Neural Combinatorial Optimization
por: Hong, Seong-Hyun, et al.
Publicado: (2024)

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling
por: Lin, Jianghao, et al.
Publicado: (2026)

Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
por: Farhat, Yehya, et al.
Publicado: (2023)

Mean-Field Path-Integral Diffusion: From Samples to Interacting Agents
por: Chertkov, Michael
Publicado: (2026)

Optimal Settings for Cryptocurrency Trading Pairs
por: Zhang, Di, et al.
Publicado: (2022)

Safe Control and Learning Using Generalized Action Governor
por: Fang, Peiyuan, et al.
Publicado: (2022)

Nonlinear Control Allocation: A Learning Based Approach
por: Khan, Hafiz Zeeshan Iqbal, et al.
Publicado: (2022)

Policy Optimization for PDE Control with a Warm Start
por: Zhang, Xiangyuan, et al.
Publicado: (2024)

Temporal Robustness in Discrete Time Linear Dynamical Systems
por: Metya, Nilava, et al.
Publicado: (2025)

Distributionally Robust Control with End-to-End Statistically Guaranteed Metric Learning
por: Wu, Jingyi, et al.
Publicado: (2025)

Constraint-Anchored Attribution: Feasibility-Certified Counterfactuals and Bonferroni-PAC Sufficient Subsets for Neural CO Policies
por: Lafifi, Sohaib
Publicado: (2026)

A Discrete-Time Switching System Analysis of Q-learning
por: Lee, Donghwan, et al.
Publicado: (2021)

Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
por: Kamboj, Ankur, et al.
Publicado: (2026)

Classical and Deep Reinforcement Learning Inventory Control Policies for Pharmaceutical Supply Chains with Perishability and Non-Stationarity
por: Stranieri, Francesco, et al.
Publicado: (2025)

Approximate Model Predictive Control for Microgrid Energy Management via Imitation Learning
por: Liu, Changrui, et al.
Publicado: (2025)

Large-scale Online Ridesharing: The Effect of Assignment Optimality on System Performance
por: Fiedler, David, et al.
Publicado: (2023)

Multi-Robot Multi-Queue Control via Exhaustive Assignment Actor-Critic Learning
por: Merati, Mohammad, et al.
Publicado: (2026)

Model Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programming
por: Bertsekas, Dimitri P.
Publicado: (2024)

The Principle of Proportional Duty: A Knowledge-Duty Framework for Ethical Equilibrium in Human and Artificial Systems
por: Prescher, Timothy
Publicado: (2025)

From MIDI to Rich Tablatures: an Automatic Generative System incorporating Lead Guitarists' Fingering and Stylistic choices
por: Bontempi, Pierluigi, et al.
Publicado: (2024)

Model Predictive Control of Hybrid Dynamical Systems
por: Sanfelice, Ricardo G., et al.
Publicado: (2026)

Nonlinear Non-Gaussian Density Steering with Input and Noise Channel Mismatch: Sinkhorn with Memory for Solving the Control-affine Schrödinger Bridge Problem
por: Bondar, Georgiy A., et al.
Publicado: (2026)

A Context-Free Smart Grid Model Using Complex System Approach
por: Amor, Soufian Ben, et al.
Publicado: (2025)

Offline Supervised Learning V.S. Online Direct Policy Optimization: A Comparative Study and A Unified Training Paradigm for Neural Network-Based Optimal Feedback Control
por: Zhao, Yue, et al.
Publicado: (2022)

A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems
por: Yin, Cheng, et al.
Publicado: (2023)