Feedback Control

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Overview

Feedback control studies how systems use measurements of their behavior to continually adjust actions, helping robots, vehicles, buildings, and industrial processes track goals and reject disturbances. Established approaches include PID and LQR, model-predictive control, and nonlinear designs based on Lyapunov functions, passivity, and control barrier functions; newer work adds reinforcement learning, learned dynamics, and Koopman models. These methods are tested in settings such as robotic manipulation and flight, HVAC and energy systems, vehicle guidance, and networked or multi-agent control, often with delays, partial sensing, actuator limits, and changing dynamics. A central challenge is gaining the adaptability of learning-based control without losing stability, safety, and verifiable performance, motivating hybrid designs with runtime safety filters and formal analysis.

Latest papers

CardsList

255 papers30 papers in the last four weeks, down 6% on the four weeks before. 0.2% of all new papers.

  1. Feedback autocratic strategies in stochastic games

    Oct 27, 2026Masahiko UedaFeedback Control

    Department of Physics, Tokyo Metropolitan University, Tokyo 192-0397, Japan

  2. Physics-Informed and Data-Driven Composite Disturbance Separation and Predictive Control for Airborne Electro-Optical Gimbals with Multiple Constraints

    Oct 26, 2026Yaokun Lu, Yifan Li, Zhixuan Zhang +3Feedback ControlDisturbance Rejection

    School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China · Hangzhou Innovation Institute of Beihang University, Hangzhou, 311115, China · School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing, 100191, China

  3. Tilt-Rotor Quadcopter with Learned Residual Control and Mode-Dependent State Estimation

    Oct 22, 2026Ninad Joshi, Prabhat KumarQuadrotor ControlFeedback Control

    Mechanical and Aerospace Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India

  4. Prescribed Performance Guided Safe Reinforcement Learning for Roundabout Navigation of Autonomous Vehicles

    Oct 20, 2026Wenhan Li, Yangrui Zhang, Hang Zhou +2Autonomous Driving PlanningRL for Autonomous Driving

    Robotics and Autonomous Systems Thrust, Systems Hub, the Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong Province, China

  5. When Does Feedback Help? Auditing Learned Voltage-Clamp Experimental Design

    Oct 20, 2026Rayan Nyaupane, Abhiram BhupatirajuActive Experimental DesignFeedback Control

    The University of Texas at Austin

  6. Velocity Optimization via Thermal Imaging Enhances Autonomous Tumor Resection

    Oct 20, 2026Naveed D. Riaziat, Jiawei Ge, Ethan Kilmer +6Surgical RoboticsFeedback Control

    Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, Maryland · Department of Pathology, Johns Hopkins Hospital, Baltimore, Maryland

  7. Glass-Box Deep Reinforcement Learning for High-Speed Flow Control

    Oct 19, 2026Ameya D. JagtapRL ControlFeedback Control

    Aerospace Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA

  8. Reinforcement Learning Controllers for Fusion Scenario Development

    Oct 19, 2026Evgeny Adishchev, Maxim Nurgaliev, Dmitry Sorokin +5Feedback ControlRL Control

    Next Step Fusion s.a.r.l.

  9. Finite-Time Capture by a Dubins Pursuer Against Unknown Evader Strategies

    Oct 18, 2026Dinesh Patra, Bhargav Jha, Ashish R. HotaFeedback Control

    Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India

  10. Learning Changes the World and Then What Was Learned has Changed: Training and Deploying Neural Networks in the Control Loop

    Oct 15, 2026Vittorio LippiDistribution ShiftFeedback Control

    Calejo Hybrid Intelligence AB, Mellansjö 109, 92592 Tärnaby, Sweden

  11. Adaptive Prescribed Performance Trajectory Tracking for Uncertain Autonomous Underwater Vehicles With Input Saturation

    Oct 14, 2026Athanasios K. Gkesoulis, Christos Vlachos, George K. Fourlas +2Robot Trajectory TrackingAdaptive Control

    The authors are with the Robotics Institute, Athena Research Center, Marousi, Greece · The authors are with the Division of Systems and Automatic Control, Department of Electrical and Computer Engineering, University of Patras, Patras, Greece · The authors are with the Department of Informatics and Telecommunications, School of Sciences, University of Thessaly, Lamia, Greece

  12. Mixed-Reality Feedback Control: Towards Blending of Control and Digital Twinning

    Oct 14, 2026Melisa Soydan, Mario GleirscherFeedback ControlDigital Twins

    Institut Polytechnique de Paris, X, Palaiseau, France · Institut Polytechnique de Paris, ENSTA, Palaiseau, France

  13. Optimizing Team Behavior via Extremum-seeking Control in Multi-agent Reinforcement Learning

    Oct 13, 2026Svar Rajankumar Patel, Kshitij JerathBehavioral Diversity in RLCooperative MARL

    Department of Computer Science, University of Massachusetts Lowell, Lowell, Massachusetts, USA · Department of Mechanical and Industrial Engineering, University of Massachusetts Lowell, Lowell, Massachusetts, USA

  14. Joint-Feasibility Margin Feedback for Bounded-Input Second-Order Control Barrier Functions

    Oct 12, 2026Siyuan Yang, Shaoming HeControl Barrier FunctionsFeedback Control

    School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China.

  15. PID-Gated Continual Prompt Adaptation Under Noisy Feedback

    Oct 12, 2026Zhentao XuPID ControlPrompt Optimization

    Independent Researcher, Sunnyvale, CA, USA

  16. Physics-guided machine learning for saturation control across variable hydraulic conditions in heap leaching

    Oct 11, 2026Sultan Alhamdan, Daniel Navia, Paulina QuintanillaPDE Surrogate ModelingPhysics-Informed ML

    Department of Chemical Engineering, University College London, London, United Kingdom · Department of Chemical and Environmental Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile

  17. Integrating AIRL-Based Reward Estimation into a Control Method Using Fuzzy Inference and Policy Gradient

    Oct 10, 2026Seiji IshiharaRL ControlReinforcement Learning

    School of Science and Engineering, Tokyo Denki University, Saitama, Japan.

  18. Noise-Induced Navigation in Non-convex Domains and Compact Manifolds

    Oct 7, 2026Karthik ElamvazhuthiFeedback ControlDynamical Systems

    independent researcher

  19. Rapid Fredholm stabilization of the Kuramoto--Sivashinsky equation with unrestricted, spatially-varying anti-diffusion

    Oct 6, 2026Luke Bhan, Miroslav Krstic, Yuanyuan ShiBackstepping ControlDynamical Systems

    University of California, San Diego, 3180 Voigt Drive, La Jolla, CA 92093, USA.

  20. Dual-Rate Force-Image Control with Model-Based Orientation Limits for Robotic Ultrasound

    Oct 5, 2026Tyler Foster, Qiang Zhang, A B M Tahidul Haque +1Robotic ControlRobotic Ultrasound

    Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA · Department of Chemical & Biological Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA · Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487, USA

  21. Demonstration Calibrated Port-Hamiltonian Retuning for Manipulation Policies

    Oct 5, 2026Yulong Yang, Fan Wu, Christine Allen-Blanchette +1Robot Policy AdaptationImpedance Control

    Princeton University · Arizona State University · Siemens Foundation Technologies

  22. Virtual model control for compliant reaching under uncertainties

    Oct 5, 2026Yi Zhang, Daniel Larby, Fumiya Iida +1Robotic ControlRobotic Manipulation

    Department of Engineering, University of Cambridge, UK.

  23. A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim

    Oct 4, 2026Cheng Siong Chin, M. Venkateshkumar, Jianhua ZhangRL ControlUnderwater Robotics

    Faculty of Science, Agriculture, and Engineering, Newcastle University Singapore, Singapore 828608, Singapore · Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India · School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266525, China

  24. PLCWorld: Benchmarking LLM-Generated PLC Programs in Closed-Loop Plant Simulation

    Oct 2, 2026Yunji Kim, Yunseok Lee, Hyunwoo Seo +2LLM-Based Program SynthesisCode Generation

    Dongguk University · MOAI technologies

  25. Decentralized Power-Optimal Coordination for Spacecraft Swarms Using Time-Varying Magnetorquer Actuation

    Oct 1, 2026Yuta Takahashi, Shin-ichiro SakaiMulti-Agent CoordinationFeedback Control

    Department of Mechanical Engineering, Institute of Science Tokyo, Tokyo, Japan · Department of Spacecraft Engineering, Japan Aerospace Exploration Agency, Kanagawa, Japan

  26. Finite-Data Safety Informativity Under Dynamic Asymmetric Actuation

    Oct 1, 2026Abhinav Sinha, Praveen Kumar Ranjan, Yongcan CaoSafety-Critical ControlRobust Control

    GALACxIS Lab, Department of Aerospace Engineering, University of Cincinnati, Cincinnati, OH 45221, USA · Unmanned Systems Lab (USL), Department of Electrical Engineering, The University of Texas at San Antonio, TX 78249, USA

  27. Admissibility-Preserving Control for Multi-Input Systems with Joint Capacity Constraints

    Sep 30, 2026Saurabh Kumar, Lohitvel Gopikannan, Shashi Ranjan Kumar +1Backstepping ControlFeedback Control

    Intelligent Systems & Control (ISaC) Lab, Department of Aerospace Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India · Guidance, Autonomy, Learning, and Control for Intelligent Systems (GALACxIS) Lab, Department of Aerospace Engineering, University of Cincinnati, OH 45221, USA

  28. DSDyn-VLA: A Dual-Stream Dynamic Manipulation Framework with Motion Perception, Future Awareness, and Realtime Correction

    Sep 30, 2026Wenhao Li, Xiu Su, Yu Han +3Feedback ControlVision-Language-Action Models

    University of Sydney · Central South University · University of California, San Diego +1

  29. ID Balancing: Stable Training of Extremely Sparse MoE via PID-Based Load Control

    Sep 30, 2026Peng Jin, Zihan Qiu, Zekun Wang +8Expert Load BalancingMixture-of-Experts Language Models

    Qwen Team, Alibaba Token Hub, Alibaba Group

  30. Residual Wrench Certification and Margin-Aware Control Synthesis for Aerial Physical Interaction

    Sep 30, 2026Abhimanyu Khadga, Abhinav Sinha, Shashi Ranjan KumarRobot Morphology-Control Co-DesignRobust Control

    Guidance, Autonomy, Learning, and Control for Intelligent Systems (GALACxIS) Lab, Department of Aerospace Engineering, University of Cincinnati, OH 45221, USA · Intelligent Systems and Control (ISaC) Lab, Department of Aerospace Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India