Engineering & Signals · Interdisciplinary & Society
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 14
Efficient Hybrid Hard--Soft Signal Temporal Logic MPC for Driving under Multimodal Uncertainty
Motion planning for automated vehicles in interactive traffic has to simultaneously ensure safety, respect traffic rules, and maintain comfortable progress under multi-modal behavior uncertainty.Jacobian State Augmented Viable Kinematic Safety Filter
Safety Filters (SF) are leveraged to design certifiably safe controllers, which ensures forward invariance on a defined safe set when the filter is feasible.Physics-guided machine learning for saturation control across variable hydraulic conditions in heap leaching
Heap-leaching hydraulics vary between regions of an ore bed, motivating fast prediction models that accommodate different material properties.AnyRank: Reliable Anytime Policy Ranking via Sequential Testing
Due to the high cost of hardware experiments, robot policies are predominantly evaluated by comparing their empirical performance on a limited number of hardware trials.Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learning
Diffusion-based policies have recently emerged as a powerful paradigm for offline reinforcement learning, but their reliance on multi-step denoising introduces substantial computational overhead and…UAV-Mounted Hybrid RIS-Assisted ISAC-RSMA: Performance Analysis with Imperfect CSI and SIC
In integrated sensing and communication (ISAC) systems, strict sensing requirements can substantially constrain the transmit power available for communication.Game-Theoretic Reinforcement Learning based Topology-Agnostic Defense for Virtual Power Plants
The rapid proliferation of distributed energy resources (DERs) aggregated by virtual power plants (VPPs) elevates cybersecurity risk by expanding the attack surface.In-Context Learning for System Identification: Probabilistic Formulation, Long-Sequence Handling, and Benchmark Validation
Traditional system identification typically involves two steps: initially, training data is processed to estimate a model of the system of interest; then, the model is used to predict outputs for…A Scalable Learned Iterative Solver for Nonlinear MPC via Temporal Decomposition
Nonlinear model predictive control (NMPC) can be applied to large nonlinear systems with complex objectives while enforcing constraints, but the cost of solving the underlying optimization problems…Asymptotic Analysis of Discrete-Time Self-Attention Dynamics in Transformers
In machine learning, a self-attention dynamics describes the attention mechanism of transformers, and is obtained treating the layer index of a transformer as time index.Goal-Oriented Bundle Management and Flow Control for Deep-Space Communications via Reinforcement Learning
Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints.ConicFlow: constrained Inference-time optimal control for flow matching models
We propose ConicFlow, which frames constrained sampling from a flow matching model at inference time as an optimal control problem that balances deviation from the pretrained trajectory against…History, Adaptation, and Hidden Gain: Two Prospective Tests of Learned Predictive Control in a Synthetic Neural Population
We study learned one-step predictive control of a synthetic population of 64 leaky integrate-and-fire neurons whose light sensitivity is scaled by a hidden factor s, using two prospective…Deep learning from a control vantage point
This article offers an overview of recent developments in deep learning from a control vantage point.Causal-fate dynamics of unrealized influence
Many dynamical systems generate influences whose consequences are not fully exhausted in the realized trajectory at the moment they arise.Autonomous thermodynamic cycles via robotic mobility and sensing
Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work.Narrow and Deep: An Ontology Tower as the Knowledge of an LLM Agent for an Industrial Equipment System
Large language model (LLM) agents are beginning to operate industrial energy equipment, and what they get right depends on what they are told about the plant.Learning structured linear dynamical systems from missing observations
We consider the problem of learning structured linear dynamical systems over convex sets $\mathcal{K}$, where only a small subset of the observations are available at each time point.RobustLDS: Learning linear dynamical systems under adversarial corruptions
We consider the problem of learning linear dynamical systems under adversarial contamination from a single trajectory of length $T$.CAPABLE: Capability-Aware Policy Adaptation via Behavioral Latent Encoding
Vision-language-action (VLA) policies assume the embodiment on which they were trained and can fail when a joint fault changes how commanded actions are physically executed.