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Systems & Control
The newest papers in Systems & Control that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
703 papers, from 31 August 2026 to 5 November 2026: 644 arXiv preprints and 59 OpenAlex records.
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Newest papers, page 21
Towards Scalable Quantum Unit Commitment in Power Systems: Encoding and Complexity Reduction Techniques
This paper develops a Quantum optimisation Unit Commitment (UC) framework that benefits from Pauli Correlation Encoding (PCE) as a qubit reduction preprocessing technique and Sample-based Quantum…PowerMarketJax: A JAX Benchmark Suite for Multi-Agent Reinforcement Learning in Power Markets
Power markets are a natural testbed for multi-agent reinforcement learning (MARL), where multiple self-interested participants repeatedly submit bids.Cascaded consensus splitting for multi-branch contingency games
Contingency games enable agents to anticipate and plan for other agents' hypothetical intents by constructing trajectories with a shared prefix and intent-dependent branches.An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis
This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constant current load across multiple heterogeneous…Stochastic World Models for Verifying Vision-Based Neural Feedback Systems
Verifying a vision-based neural feedback system requires a model of the observations its controller acts upon.Unified Optimality Conditions for Stochastic Optimal Control in the Rough Path and Itô Frameworks
Stochastic differential equations (SDEs) can be studied via Itô calculus and rough path theory.An Empirical Study of Architectural Shift from Traditional to AI-Enabled Simulink Controllers
Effective AI adoption in cyber-physical systems (CPS) depends on embedding design knowledge into engineering practice.Onboard Vision and MPC Navigation for Underwater Robots: An Open BlueROV2 Platform for Multi-Robot Experiments & Docking
Autonomous underwater robots require robust perception, estimation and control to operate in confined environments.A Weak Notion of Symmetry for Control Systems
Symmetry (or invariance) is a powerful structural property that enables efficient, effective solutions for estimation and control.When World Models Lie: Adaptive Safety Analysis Under Wrong Imaginations
World models offer a powerful substrate for safety reasoning in high-dimensional robotic systems, but they are also fallible: their predictions can be biased, miscalibrated, or confidently wrong.Strategically Robust Game-Theoretic Multi-Agent Trajectory Optimization
Aviation authorities worldwide expect Advanced Air Mobility (AAM) traffic management to be decentralized among service providers, requiring AAM flights to autonomously plan trajectories by…Jev thinks "I don't know'', but doesn't say it: Introducing Sys1Cal-v1 Dataset for Probability Calibration
The appearance of Jev marked the era of System One Models, foundation models that return structured decisions with probability distributions rather than text.Adaptive Safety Filtering for Frozen ACC Policies via Conformal Residual Calibration
Frozen adaptive cruise control (ACC) policies can violate constraints when deployment dynamics differ from their training conditions.Manifold-Stable Flow Matching
Flow matching (FM) learns generative dynamics through velocity regression.LQR-ArUco Fusion: Robust Hierarchical Control for Navigation and Asymmetric Manipulation in Two-Wheeled Robots
We propose a hierarchical control framework to address severe dynamic instabilities and navigational drift that arise when a two-wheeled inverted pendulum (TWIP) robot attempts asymmetric object…Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control
We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances.Preferent Compression Bounds Are Tight
The lack of rigorous safety and performance certificates remains a key bottleneck to the deployment of modern learning-based methods.PowerZooJax: A JAX-based Power System Benchmark for Reinforcement Learning
Power system operation is a safety-critical sequential decision-making problem, making it a natural testbed for reinforcement learning (RL).MagNav: A Dual-Core Magnetic Track Guidance Framework for Lighting-Invariant Navigation in Two-Wheeled Robots
Two-Wheeled Inverted Pendulum (TWIP) robots are useful for studying how to control systems that are naturally unstable and have fewer actuators than degrees of freedom.Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs
Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task.