Papers nuevos sobre Sistemas de control
109 papers nuevos sobre sistemas de control en los últimos 7 días, dentro de Robótica e ingeniería. Acá están los 50 que Pipette considera más valiosos, con el resultado principal en palabras de sus autores.
Lo mejor de la semana
Collocated Shape Regulation for Soft Robots
We show that regulating only the actuated coordinates, through collocated shape control, achieves provably stable convergence of those coordinates and, under an explicit compatibility condition, of the entire robot shape.
PreprintDice ser un gran avanceRAYA: Learning Where and When to Intervene for Robot Recovery
Building on this, we present RAYA, a hybrid learned-analytic framework that places a learned finite-horizon recoverability margin inside an optimal controller with hard constraints and pairs it with a bounded learned scheduler that shifts task weights to facilitate recovery.
PreprintUso en el mundo realGA-Agent: Large Language Models as Hyperparameter Optimizers for Evolutionary Controller Synthesis
We propose GA-Agent, which decouples these modes.
PreprintUso en el mundo realMerging Large Language Models and Battery Physics for User-Aware Electric Vehicle Driving Management
This paper proposes a hybrid physics-artificial intelligence framework that integrates a Large Language Model (LLM) as a high-level behavioral reasoning layer within a physics-driven supervisory architecture.
PreprintUso en el mundo realNetwork Design against the Bullwhip Effect in Complex Supply Chains
We show that on a directed acyclic network every response from demand to orders is a sum over paths of products of nodal responses, so that the stability and stability margins of the network are determined by those of its individual nodes, and that a node which splits its orders across routes of different lengths gains margin it can spend on a higher gain and a faster response.
PreprintAdaptive Uncertainty-Aware Modeling and Stochastic Radial Basis Function Predictive Control for Personalized Fluid Resuscitation
This paper presents a novel framework integrating Bayesian physiological modeling with optimal control strategies to achieve uncertainty-aware, personalized hemodynamic regulation during fluid resuscitation.
PreprintUso en el mundo realLIMBO: Learning and Internalizing Model-Free Barrier Objectives for Agile and Safe Whole-Body Control
We present LIMBO, a framework for synthesizing a state-action control barrier function and distilling its safety structure into a task policy.
PreprintUso en el mundo realKoopman-Accelerated Model-Based Diffusion for Real-Time Robot Control
To address this limitation, this paper proposes bilinear Koopman model-based diffusion (BK-MBD).
PreprintUso en el mundo realLEMCA: LLM-Guided Synthesis of Efficient Mode-Switching Control Architectures
To facilitate the design of performant yet efficient MSCs, we propose LLM-Guided synthesis of Efficient Mode-Switching Control Architectures (LEMCA).
PreprintAfirmaciones fuertes, leer con cuidadoUso en el mundo realSafe Receding Horizon Mixed-Integer Differentiable Predictive Control for Degradation-Aware Battery Dispatch
We present a safe receding-horizon mixed-integer differentiable predictive control methodology for residential battery energy storage dispatch that combines neural-network speed with recursive feasibility guarantees.
PreprintUso en el mundo realDistribution-Free Budgeted Stealthy Attack Scheduling for Remote State Estimation
We establish exact pathwise stealth against every magnitude-measurable detector, for any firing rule and innovation law; a finite-sample distribution-free bound on the mean firing rate, with almost-sure budget attainment under stationarity and ergodicity; and a steady-state degradation identity linear in a single scalar energy capture , maximized by the same order statistic that delivers the budget guarantee.
PreprintUso en el mundo realModel-Free Control for Residential Heating: Deployment and Simulation of Nonlinear Data-Enabled Predictive Control
Each of the DPC controllers consumes significantly less energy than the hysteresis controller, amounting to roughly over the season, validating the use of DPC.
PreprintUso en el mundo realStochastic MPC under Heavy-Tailed Disturbances: An Extreme Value Theory Approach
This paper develops an SMPC formulation for linear systems under heavy-tailed disturbances that is only assumed to be regular varying, replacing these approaches with an explicit extreme value theory (EVT) characterization of the tube error tail that is asymptotically exact.
PreprintUso en el mundo realNew perspectives for the fitness fatigue model: how to revisit questions about the science of sports training from the perspective of systems control theory
The state representation makes it possible to study the controllability, observability and diagnosability of a system (i.e, the athlete) and thus to formally answer the three previous practical questions.
PreprintBarrierFormer: Transformer-Guided Predictive Barrier Enforcement for Safe Robot Control
We propose BarrierFormer, a barrier-supervised transformer framework that addresses these limitations by encoding rollout-level CBF constraints in learning a model-free safe policy.
PreprintUso en el mundo realStability-Aware Imitation Learning from Model Predictive Control for Autonomous Vehicle Lateral Control: Exact Q-Loss and a Novel Training Procedure
This paper develops a certified imitation-learning framework for approximating model predictive control (MPC) policies with feedforward neural controllers and validates it on autonomous-vehicle lateral control.
PreprintUso en el mundo realPINGU: Extending Air-Bearing Spacecraft Emulators with Open-Source Actuators and Learned Control for Contact-Rich Proximity Operations
The results show that these additions extend an ATMOS-class emulator into the contact-rich regime and bridge classical optimal control and reinforcement learning on one reproducible platform.
PreprintA Mean-Field Approach for Safe Routing of Multi-Destination Urban Air Mobility Networks
A key contribution of this work is the formal proof of the positive invariance of the queue-free state space.
PreprintUso en el mundo realStability-aware Residual Reinforcement Learning Framework for Robotic Manipulator Disturbance Compensation
This study proposes a residual reinforcement learning DOB framework that pairs an analytical observer with an RL policy.
PreprintUso en el mundo realTilt as a Certified Resource: Preserving Motor Wrench-Rate Authority on Articulated Multirotors
This paper uses active morphology to break the degeneracy, treating servo tilt as a geometric resource supplying authority-recovery directions unavailable to static rotors.
PreprintUso en el mundo realPhysics-Informed Neural Network Surrogates with Polynomial Chaos-Based Uncertainty Propagation for Stochastic Model Predictive Control
We present a unified framework that couples Physics-Informed Neural Networks (PINNs) with Polynomial Chaos Expansion (PCE) to construct a fast and differentiable surrogate.
PreprintReward-Rate Congestion Games and Replicator--Dinkelbach Dynamics
We develop a Dinkelbach-based framework in which, for every fixed Dinkelbach parameter, the transformed game is an exact potential game.
PreprintSame World, Different Knowledge: When Isolated Audits Misjudge World-Model Repairs
A repair favored under an isolated input fault can be inferior when deployed modules share the faulty information.
PreprintUso en el mundo realLEAP-CBF: A Safety Filter for Uncertain Systems with Least-Effort Adversarial Potentials
In this work, we propose a new approach to solve these challenges by introducing Least-Effort Adversarial Potentials (LEAP), a certificate that quantifies the robustness of a given state against disturbances in terms of the effort required by the disturbance to cause failure.
PreprintUso en el mundo realSafety-Filtered Distributed Koopman-MPC
The full controller is collision-free in 20/20 matched trials and reaches 160/160 robot goals; predictive Koopman-MPC without the final projection is collision-free in 1/20 trials.
PreprintUso en el mundo realTwo-impulse Rendezvous Planning about Thrusting Spacecraft on
We address this limitation with a relative motion framework on the Lie group that encodes position, velocity, and attitude in a unified geometric state.
PreprintUso en el mundo realOptimal Trajectory Generation for Improved Magnetic Navigation
This paper proposes an optimal trajectory design framework for magnetic navigation that maximizes information content along the flight path.
PreprintUso en el mundo realRisk-Aware Online Conformal State Probing
We propose online conformal state probing (OCSP), an action and probing policy that certifies worst-case reliability levels without relying on distributional assumptions.
PreprintUso en el mundo realTractable Reinforcement Learning for Full Class of Signal Temporal Logic Specifications Using Spatiotemporal Tube Reward
The proposed framework offers a history-free, computationally efficient approach to learn continuous control policies that ensure robust satisfaction of specifications while strictly adhering to system input constraints.
PreprintAfirmaciones fuertes, leer con cuidadoUso en el mundo realGeneralizable Optimal Control with Transformers: Closed-Loop Certification and Near-Optimality Guarantees
Our main result is a probabilistic certificate for finite-horizon closed-loop near-optimality.
PreprintBarrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting
On coordinated-turn and planar multirotor models, exact lifting improves certified coverage in both methods: at matched sample sizes, lifted successive-barrier synthesis achieves higher coverage with fewer barriers and lower computational cost, while lifted joint barrier synthesis provides higher coverage and lower computational cost than the finest tested piecewise resolution.
PreprintUso en el mundo realConstraint-Unified MPC for Over-Actuated Surface Vehicles with Post-Detection Fault Reconfiguration
We report a deployed system in which trajectory tracking, thrust allocation, and the per-thruster force and rate limits are resolved in a single quadratic program over the per-thruster commands, with fault reconfiguration entering through one binary flag per thruster from an external detector.
PreprintUso en el mundo realIterative Learning Control of the Cooling Rate in a Dual-Laser Powder Bed Fusion Process
Results show that the controller drives the plant cost down by over an order of magnitude and reaches a tight band of low-cost solutions across seeds, while model-only feedforward optimization stalls at a substantially higher plant cost despite appearing to converge on the surrogate.
Preprint con versión publicadaUso en el mundo realConformalized Kalman Filters for State Estimation with Trustworthy Confidence Regions
In this work, we develop a conformal prediction (CP) framework for equipping Kalman-type filters with statistically reliable confidence regions.
PreprintVision-Based Control of a Tether-Suspended Aerial Radiation Sensing Payload
We therefore present a vision-based control approach for an aerial sensing payload suspended on a tether beneath a heavy-lift drone.
PreprintUso en el mundo realA Novel Path-Tracking Algorithm for Automated Tractor-Trailer Forward and Backward Maneuvers
The proposed method combines a lateral control law applied at the trailer level with a short-horizon predictive adjustment of the tractor steering angle, ensuring stable convergence toward the desired path in both forward and backward motion.
PreprintUso en el mundo realCollective Tube Model Predictive Control With Distribution-Free Joint Safety Certificates
This paper develops collective tube MPC (CT-MPC), where the calibrated uncertainty object is the finite-horizon prediction-error trajectory.
PreprintLearning Dissipative Dynamics with Dissipativity-by-Construction Discrete-Time Neural Networks
Through a constrained parameterization and a dedicated training procedure, the proposed model guarantees incremental dissipativity by construction rather than through regularization.
Preprint con versión publicadaUso en el mundo realSafety-Constrained Model Predictive Control for an Omnidirectional Walking Assistive Robot Using Control Barrier Function
Comparative results show that the CB-MPC architecture significantly reduces energy consumption and mechanical work (p < 0.01) without compromising motion smoothness, while also decreasing the number of obstacle collisions.
PreprintUso en el mundo realThe Minkowski Wrap: A Relativistic Speed Limiter
The proposed method transforms the classical double-integrator dynamics into a "wrapped" system that respects velocity bounds without the need for clipping, offering an explicit nonlinear feedback control strategy conducive to safety applications.
PreprintUso en el mundo realGray-Box Model Predictive Control for Articulated Dump Trucks via Gaussian Process Learning of Sideslip
We show that the gray-box model can predict the sideslip angle and, consequently, the vehicle's lateral velocity, thereby improving the MPC's prediction performance.
PreprintUso en el mundo realSafety Control of a Hyper-redundant Robot via Adaptive Weighted Control Barrier Functions
To address these issues, this work proposes a weighted control barrier functions (W-CBFs) framework that enforces safety constraints while reducing tracking errors caused by uneven loading.
PreprintUso en el mundo realA Switched Adaptive Control Framework for Aerial Manipulators Under Dynamic Transitions
We propose a switched-based adaptive control framework for aerial manipulators not relying on a priori knowledge of the vehicle-manipulator couplings and of state-dependent uncertainties.
PreprintModel-Free Current Control of Permanent Magnet Synchronous Motors via ESO-Based Disturbance Feedforward and Data-Driven H-infinity Residual Feedback
This paper proposes a model-free current control method for permanent magnet synchronous motors (PMSMs) based on disturbance feedforward and residual feedback.
PreprintUso en el mundo realOn a Closed-Loop Controller for the Coevolutionary Model of Actions and Opinions via Broadcasting Information
Then, we introduce a feedback control law that, using information on the state of the system, dynamically revises the target set, reducing the effort needed to achieve the objective while guaranteeing convergence to the desired consensus state.
PreprintA bioinspired internal model-based online estimator for planar pursuit
This paper develops a bioinspired internal model-based estimator for reconstructing those quantities from partial sensory observations and known self-motion.
PreprintUso en el mundo realSafety-Critical Control under Uncertainty via Adaptive Conformal Quantile Prediction Intervals
In this paper, we introduce a novel safe control framework with adaptive uncertainty quantification that constructs calibrated and state-dependent prediction intervals to enable high-probability safety guarantees, while improving constrained control performance.
PreprintUso en el mundo realControl Barrier Functions for Safe Free-Flying Robotic Spacecraft Operations in Tumbling Target Capture
This paper presents a modular control barrier function (CBF) framework for safe free-flying robotic spacecraft operations during tumbling target capture.
PreprintUso en el mundo realScenario MPC with STL Specifications and Pareto-Based Feasibility Repair
In this paper, we propose a model predictive control (MPC) framework that treats feasibility repair as a Pareto optimization problem to explicitly characterize tradeoffs among agent objectives.
PreprintUso en el mundo realAccelerating Branch MPC with Two-Level Parallel Direct Solves on GPUs
We present a GPU-accelerated direct linear solver for branch MPC formulations in which all trajectories share a single root decision node and evolve independently thereafter.
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