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Learning-Based Control: A Tutorial and Some Recent Results
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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New Results in Cooperative Adaptive Optimal Output Regulation
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A Review on Resilient Reinforcement Learning for Linear Cyber-Physical Systems
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Data-driven cooperative output regulation of multi-agent systems under distributed denial of service attacks
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Value iteration algorithm for continuous-time linear quadratic stochastic optimal control problems
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Learning-based adaptive optimal output regulation of linear and nonlinear systems: an overview
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A Lyapunov characterization of robust policy optimization
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A tractor-trailer parking control scheme using adaptive dynamic programming
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Timing faults and attacks
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Policy Iteration-Based Learning Designs for Linear Systems With Prescribed Performance
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Adaptive optimal output regulation of linear discrete-time systems based on event-triggered output-feedback
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Resilient reinforcement learning and robust output regulation under denial-of-service attacks
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Adaptive optimal control of continuous-time nonlinear affine systems via hybrid iteration
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Incremental reinforcement learning and optimal output regulation under unmeasurable disturbances
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On the effect of clock offsets and quantization on learning-based adversarial games
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Learning-based adaptive optimal control of linear time-delay systems: A value iteration approach
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Fixed-time learning for safe time-critical verification using reachability analysis
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Non-zero-sum games in continuous-time nonlinear systems: Multiplayer cascaded solutions
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Adaptive optimal output regulation of polynomial systems via internal model principle
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Value iteration and adaptive optimal output regulation with assured convergence rate
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Disturbance observers and extended state observers for marine vehicles: A survey
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Revolutionizing construction: A cutting-edge decision-making model for artificial intelligence implementation in sustainable building projects
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Robust Reinforcement Learning for Stochastic Linear Quadratic Control with Multiplicative Noise
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Learning-Based Control of Multiple Connected Vehicles in the Mixed Traffic by Adaptive Dynamic Programming
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Policy Iteration and Event-Triggered Robust Adaptive Dynamic Programming for Large-Scale Systems
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A Value Iteration Approach to Adaptive Optimal Control of Linear Time-Delay Systems
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Resilient Learning-Based Control for Partially Observable Systems Under DoS Attacks
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Decentralised adaptive learning-based control of robot manipulators with unknown parameters
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Data-driven control for continuous-time linear systems via integral reinforcement learning: An overview
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Enhancing hierarchical learning of real-time optimization and model predictive control for operational performance
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Inverse reinforcement learning by expert imitation for the stochastic linear–quadratic optimal control problem
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Prescribed-rate target tracking for time-delayed systems using output measurements
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Model-based and model-free designs for an extended continuous-time LQR with exogenous inputs
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Neural operators for PDE backstepping control of first-order hyperbolic PIDE with recycle and delay
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Reinforcement learning for linear exponential quadratic Gaussian problem
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Small-disturbance input-to-state stability of perturbed gradient flows: Applications to LQR problem
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Processor-in-the-Loop Validation of a Gradient Descent-Based Model Predictive Control for Assisted Driving and Obstacles Avoidance Applications
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Toward Resilience in Mixed Critical Industrial Control Systems: A Multi-Disciplinary View
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Data Driven Linear Quadratic Gaussian Control Design
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Output Feedback Control for Deterministic Unknown Dynamics Discrete-Time System Using Deep Recurrent Q-Networks
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Resilient Control of Nonlinear Uncertain Systems Under Denial-of-Service Attacks: A Learning-Based Approach
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A model-free approach to approximate the solution of time-varying optimal control based on Bezier control points technique
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Value Iteration and Data-Driven Optimal Output Regulation of Linear Continuous-Time Systems
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Data-Driven Adaptive Optimal Control of Mixed-Traffic Connected Vehicles in a Ring Road
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Extremum Seeking and Adaptive Dynamic Programming for Distributed Feedback Optimization
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Scalable Decomposition for Stability Analysis of Feedback Systems with High-Dimensional Neural Network Components
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Learning-based Event-triggered Adaptive Optimal Output Regulation of Linear Discrete-time Systems
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Adaptive Optimal Control for Discrete-Time Linear Systems via Hybrid Iteration
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Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions
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Learning-Based State Estimation for Automated Lane-Changing
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Experimental Results in Cyber-Physical Transportation Systems: A Case Study in Cybersecurity
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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems with Application to Power Systems
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Learning Distributed Stabilizing Controllers for Multi-Agent Systems
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Value Iteration for Linear Quadratic Optimal Control of Single-Input Single-Output Systems via Output Feedback
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A Small-Gain Look at Cyber-Physical Security
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Policy Iteration with Non-Asymptotic Convergence for Systems with Random Parameters
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Learning-Based Balance Control of Wheel-Legged Robots
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Learning One-Step Inverse for Performance Improvement of Nonlinear Control Systems: Application to Quadrotor Control
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Adaptive Optimal Control of Continuous-Time Linear Systems via Hybrid Iteration
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Robust Policy Iteration for Continuous-Time Linear Quadratic Regulation
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Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic Systems
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Robust Output Regulation and Reinforcement Learning-Based Output Tracking Design for Unknown Linear Discrete-Time Systems
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Learning-Based Adaptive Optimal Control of Linear Time-Delay Systems: A Policy Iteration Approach
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Adaptive Optimal Control of Unknown Nonlinear Systems via Homotopy-Based Policy Iteration
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Robust Reinforcement Learning for Risk-Sensitive Linear Quadratic Gaussian Control
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Adaptive Linear Quadratic Control for Stochastic Discrete-Time Linear Systems With Unmeasurable Multiplicative and Additive Noises
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Robust Stability and Near-Optimality for Policy Iteration: For Want of Recursive Feasibility, All is Not Lost
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Resilient Control Under Denial-of-Service and Uncertainty: An Adaptive Dynamic Programming Approach
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Safety and Optimality in Learning-Based Control at Low Computational Cost
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Adaptive-Dynamic-Programming-Regulated Extremum Seeking for Distributed Feedback Optimization
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Learning and Control From Similarity Between Heterogeneous Systems: A Behavioral Approach
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Robust Policy Iteration of Uncertain Interconnected Systems With Imperfect Data
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Online Policy Iteration Algorithms for Linear Continuous-Time H-Infinity Regulation With Completely Unknown Dynamics
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Event-Triggered Robust Adaptive Dynamic Programming With Output Feedback for Large-Scale Systems
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Learning-Based Adaptive Optimal Control for Flotation Processes Subject to Input Constraints
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Data-Driven Combined Longitudinal and Lateral Control for the Car Following Problem
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Hamiltonian-Driven Adaptive Dynamic Programming With Approximation Errors
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Data-Driven Steering Control for Heterogeneous Autonomous Vehicle Platoons via Interval Excitation-Based Learning Approach
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Hybrid Iteration ADP Algorithm to Solve Cooperative, Optimal Output Regulation Problem for Continuous-Time, Linear, Multiagent Systems: Theory and Application in Islanded Modern Microgrids With IBRs
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A Reinforcement-Learning, Optimal Approach to In Situ Power Hardware-in-the-Loop Interface Control for Testing Inverter-Based Resources: Theory and Application of the Adaptive Dynamic Programming Based on the Hybrid Iteration to Tackle Uncertain Dynamics
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A Unified Framework for Data-Driven Optimal Control of Connected Vehicles in Mixed Traffic
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Model-Freeλ-Policy Iteration for Discrete-Time Linear Quadratic Regulation
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Semiglobal Suboptimal Output Regulation for Heterogeneous Multi-Agent Systems With Input Saturation via Adaptive Dynamic Programming
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Compound Learning-Based Model Predictive Control Approach for Ducted-Fan Aerial Vehicles
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Safe Physics-Informed Machine Learning for Optimal Predefined-Time Stabilization: A Lyapunov-Based Approach
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Value Iteration for Stochastic LQR With Convergence Guarantees
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A Fully Data-Driven Value Iteration for Stochastic LQR: Convergence, Robustness, and Stability
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A Secure Robot Learning Framework for Cyber Attack Scheduling and Countermeasure
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Prescribed-Time Observer-Based HI-RL Secure Output Tracking Control for Heterogeneous MASs Under DoS Attacks
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A reinforcement learning approach to problem solving for time-varying quadratic optimal control with unknown dynamics
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Learning-Based Robust Control Policy Design for Vehicular Navigation via Ultra-Wideband Communication
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PI Algorithm for LQR Optimal Control Problem of Distributed Time-Delay System
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Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation
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Learning Adaptive Optimal Controllers for Linear Time-Delay Systems *
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Towards Mitigating Sim2Real Gaps: A Formal Quantitative Approach
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A Systematic Review of Learning-Based Control: Theory and Applications
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Reinforcement Learning for Linear Optimal Control Using a Modified Newton-Kleinman Method
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Perception-Guided Reinforcement Learning for Autonomous Lane Changing
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Fault-Tolerant Optimal Spacecraft Attitude Maneuver: An Incremental Model Approach
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A Survey on Learning-Based Model Predictive Control: Toward Path Tracking Control of Mobile Platforms
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Advances in Active Surface Shape Control for Segmented Primary Reflectors in Radio Telescopes
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Output Feedback Control for Deterministic Unknown Dynamics Discrete-Time System using Deep Recurrent Q-Networks
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Output Feedback Control for Deterministic Unknown Dynamics Discrete-Time System using Deep Recurrent Q-Networks
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Estimation-free Prediction Algorithms
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Chandrasekhar-type Algorithms with Gain Elimination
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