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 3
Towards an Optimal Control Foundation of Early Exits - Turnpikes and ResNets
The feed-forward propagation through neural networks is crucial for training and inference.OperAItor: An Agentic Framework for Fault-Tolerant Operation of Chemical Processes
OperAItor, an open-source framework for developing and evaluating large language model agents for supervisory fault management in chemical processes.Learning curves in natural and artificial systems
A general mathematical model of experience formation is considered, in which the learning level is defined as the probability that the next value of the uncertainty factor has already been mastered…Finding optimal measurement sequences for broken or constrained measuring devices
Measuring devices do not always function perfectly due to fatigue, damage, or malfunction.Touching Projected Agents through the DAT Screen -System Design and Questions of Interaction Boundaries-
Touching a virtual agent involves more than detecting a finger on a display: the contact surface can deform and resist the user's push, and the agent can respond to that action.Central pivot point control of a body-attached spring-mass runner: periodic gaits, stabilization, template embedding and approximate analytic return maps
The spring-loaded inverted pendulum (SLIP) describes the center-of-mass (COM) motion of runners but has no trunk.Neural Integral Control Barrier Functions for Agile Collision Avoidance
Control barrier functions (CBFs) are a standard way to keep a planner inside a safe set, but they assume control affine dynamics, a barrier function given in closed form, and a known nominal…When Is Tracking Affordable? A Movement-Budget Feasibility Threshold for Dynamic Regret
Dynamic regret measures an online learner against a moving comparator, and standard analyses assume the learner may move freely at every round.Efficient Detailed Scheduling of Multiproduct Pipelines using Action-Decoupled Deep Reinforcement Learning
Multiproduct pipelines transport refined products to delivery stations in sequential batches, and their detailed scheduling must meet market demand while respecting nonlinear hydraulic constraints.A Universal Policy Wrapper With Guarantees
Many control tasks require driving the system into a prescribed goal set and subsequently keeping it there.Control Foundation Models across Changing Block Diagrams: Generalizing Time-Series Prediction to Dynamic Graphs
In the prediction and control of physical systems, combining records from different experiments and operations is expected to supply information that no single experiment provides on its own.BeyondContact: A Reinforcement Learning Framework for Airflow-Based Non-Contact Manipulation
Contact-based robotic manipulation is constrained by end-effector reachability and the mechanical properties of objects.Safe-Ballbot: Tilt-Consistent MPC with Control Barrier Functions for Ballbot Navigation
Ball-balancing robots (ballbots) must lean to accelerate, and the lean is limited by the wheel torques and by safety.Non-Coherent Over-the-Air Distributed Consensus: Algorithm Design and Power Control Optimization
Non-coherent over-the-air (NCOTA) aggregation offers a scalable and communication-efficient approach to distributed average consensus in wireless networks, without requiring instantaneous channel…Beyond GNSS: Leveraging LEO Satellite Signals of Opportunity for Doppler Positioning
Large constellations of low Earth orbit (LEO) satellites provide ubiquitous global connectivity; yet, their rapid motion introduces significant Doppler shift effects.A Bayesian Framework for Safe Optimal Control of Unknown Systems from Input-Output Data
As control engineering is applied to increasingly complex systems, learning-based control, which uses empirical data to reduce the reliance on first-principles models, has emerged as a promising…Delay-Certified Readiness Barriers for Overactuated Multirotor Allocation Without Lipschitz Constants
Overactuated multirotors can produce the same wrench with many rotor-speed combinations, some of which leave the vehicle unable to change its wrench quickly, e.g., to reject a gust.D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Reward Models
Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in…Pixel-UMI: Learning Environment-Aware Whole-Body Manipulation from Sensorized Human Demonstrations
Sensorized human demonstrations offer scalable data for mobile manipulation, but embodiment differences complicate policy learning.Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation
General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning.