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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 12
Robust Multi-Agent Pursuit with Preemptive Communication via Reachability-Based Control Barrier Functions
Safe multi-agent coordination typically assumes what real-world, deployed, resource-constrained robots cannot provide: continuous, perfect state sharing.Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines
When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while adhering to legal constraints.Online Constraint Optimization-Based Indirect-Adaptive Robust Control for Autonomous Vehicles with Unknown Friction
Friction uncertainty is a significant challenge for autonomous vehicle control, undermining feasibility and performance.Comprehensive Comparisons of Reinforcement Learning Algorithms in Autonomous Driving
This paper presents a comprehensive comparison of four representative reinforcement learning (RL) methods in autonomous vehicle (AV) decision-making, including: Fitted Value Iteration (FVI), Rollout…Runtime Monitoring of Supermartingale Certificates
Supermartingale certificates formally guarantee temporal properties of discrete and continuous-time stochastic dynamical systems.Mixed-Reality Feedback Control: Towards Blending of Control and Digital Twinning
Technologies, such as co-simulation, in particular, digital twins (DTs) are used for comprehensive and reliable prototyping, verification and validation (V&V) of control systems.Sequential Learning-Based Physics-Informed Neural Network Modeling for Parameter Estimation on a Power Converter
A staged physics-informed neural network (PINN) is proposed for identifying the inductance, capacitance and parasitic resistances of a DC buck converter from time-domain data.Enabling Tidying Tasks in Robotic Vacuum Cleaners via a Geometry-Induced Self-Locking Deployable Linkage
Robotic vacuum cleaners must extend their functionality within tight limits on size, cost, and durability.Adversarial Reinforcement Learning for Robust Planetary Landing
Deep reinforcement learning (DRL) policies for planetary landing and other aerospace guidance, navigation, and control tasks are commonly trained under randomized disturbances to improve robustness.VIGOR-MPC: Vision-Guided Objective Regulation MPC
Controlling an agent in an environment solely perceived through onboard vision is challenging: perception yields noisy, variable-length, and partially occluded context, while onboard compute is…The Physics Is the Network: Fast, Training-Free Neural Emulation
Neural emulation need not require learning a substitute for known physics.Navigation by Skylight Polarization via Rayleigh Model Optimization on a Road Vehicle
Reliable absolute heading estimation is critical for road-vehicle navigation, particularly when magnetic, inertial, or GNSS-based references are degraded.A Response to the Reply Presented in "A Fair Comparison of Sliding-Mode and Immersion-and-Invariance Observers"
In response to the reply presented in [Muñoz-Vázquez and Sánchez-Torres(2026)], this technical report extends the experimental evaluation of position-feedback velocity observers and adaptive…Clarity-Driven Adaptive Mission Planning for a Solar-Powered Autonomous Surface Vessel
This paper presents a comprehensive methodology, backed by simulation and experimental results, for an adaptive mission planning strategy that is mathematically grounded in the maximization of the…Optimally Trading Energy for Information through Speed Trajectory Optimization of Sustainably Powered Mobile Robots
Sustainably powered mobile robots enable long-duration observational missions by harvesting energy from the environment.Planning to Learn: Real-Time Robust Adaptive Control on the GPU with Guaranteed Future Learning
Robust adaptive control is vital for keeping robots safe while actively reducing uncertainty in unfamiliar settings.Adaptive Prescribed Performance Trajectory Tracking for Uncertain Autonomous Underwater Vehicles With Input Saturation
Accurate trajectory tracking is essential for autonomous underwater vehicles operating with uncertain hydrodynamics and limited thruster authority.On the Complexity of Linear Programs with Parametric Constraint Matrices
While sensitivity analysis for linear programs with parametric right- hand side vectors is well established, cases involving parametric constraint matrices remain less explored.Information-based Unified Design Framework for NMR Magnetic Tracking System
Nuclear magnetic resonance (NMR) magnetic tracking offers a promising alternative to magnetic resonance imaging (MRI)-based localization for medical robotic guidance.AgentStripes: An Evidence-Graded Maturity Model for AI Agents
Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the controls that make it reliable, safe and…