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Data-driven Economic NMPC using Reinforcement Learning

arXiv 1904.04152 ↗First posted 8 Apr 2019eess.SY cs.SYcited by 55

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Abstract (arXiv)

Reinforcement Learning (RL) is a powerful tool to perform data-driven optimal control without relying on a model of the system. However, RL struggles to provide hard guarantees on the behavior of the resulting control scheme. In contrast, Nonlinear Model Predictive Control (NMPC) and Economic NMPC (ENMPC) are standard tools for the closed-loop optimal control of complex systems with constraints and limitations, and benefit from a rich theory to assess their closed-loop behavior. Unfortunately, the performance of (E)NMPC hinges on the quality of the model underlying the control scheme. In this paper, we show that an (E)NMPC scheme can be tuned to deliver the optimal policy of the real system even when using a wrong model. This result also holds for real systems having stochastic dynamics. This entails that ENMPC can be used as a new type of function approximator within RL. Furthermore, we investigate our results in the context of ENMPC and formally connect them to the concept of dissipativity, which is central for the ENMPC stability. Finally, we detail how these results can be used to deploy classic RL tools for tuning (E)NMPC schemes. We apply these tools on both a classical linear MPC setting and a standard nonlinear example from the ENMPC literature.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Apr 2019.

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Citing papers per year: 2021: 9; 2022: 5; 2023: 9; 2024: 9; 2025: 14; 2026: 9.

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  1. 2023Physics-Informed Machine Learning for Modeling and Control of Dynamical Systemscited by 28
  2. 2025Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classificationcited by 19
  3. 2021Safe Exploration in Model-based Reinforcement Learning using Control Barrier Functionscited by 8
  4. 2021MPC-based Reinforcement Learning for Economic Problems with Application to Battery Storagecited by 7
  5. 2021Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learningcited by 7
  6. 2023End-to-End Reinforcement Learning of Koopman Models for Economic Nonlinear Model Predictive Controlcited by 6
  7. 2024Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systemscited by 6
  8. 2021Regret Analysis of Learning-Based MPC with Partially-Unknown Cost Functioncited by 5
  9. 2023Learning-based MPC from Big Data Using Reinforcement Learningcited by 5
  10. 2024Model Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programmingcited by 5
  11. 2025Differentiable Nonlinear Model Predictive Controlcited by 5
  12. 2021Stability-Constrained Markov Decision Processes Using MPCcited by 4
38 more
  1. 2022Evaluation of MPC-based Imitation Learning for Human-like Autonomous Drivingcited by 4
  2. 2023UAV Path Planning Employing MPC- Reinforcement Learning Method Considering Collision Avoidancecited by 4
  3. 2024Reinforced Model Predictive Control via Trust-Region Quasi-Newton Policy Optimizationcited by 4
  4. 2024AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Controlcited by 4
  5. 2023Learning-Aided Warmstart of Model Predictive Control in Uncertain Fast-Changing Trafficcited by 3
  6. 2024Flipping-based Policy for Chance-Constrained Markov Decision Processescited by 3
  7. 2025MPCritic: A plug-and-play MPC architecture for reinforcement learningcited by 3
  8. 2025Generative AI for Autonomous Driving: A Reviewcited by 3
  9. 2025Model Predictive Control-Guided Reinforcement Learning for Implicit Balancingcited by 3
  10. 2021A Reinforcement Learning-based Economic Model Predictive Control Framework for Autonomous Operation of Chemical Reactorscited by 2
  11. 2021Proximal Policy Optimization for Tracking Control Exploiting Future Reference Informationcited by 2
  12. 2022Quasi-Newton Iteration in Deterministic Policy Gradientcited by 2
  13. 2023Reinforcement Learning with Model Predictive Control for Highway Ramp Meteringcited by 2
  14. 2023MPC-Inspired Reinforcement Learning for Verifiable Model-Free Controlcited by 2
  15. 2024Driving from Vision through Differentiable Optimal Controlcited by 2
  16. 2024A Safe and Efficient Self-evolving Algorithm for Decision-making and Control of Autonomous Driving Systemscited by 2
  17. 2025ZipMPC: Compressed Context-Dependent MPC Cost via Imitation Learningcited by 2
  18. 2025Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)cited by 2
  19. 2021Approximate Robust NMPC using Reinforcement Learningcited by 1
  20. 2022MPC-based Imitation Learning for Safe and Human-like Autonomous Drivingcited by 1
  21. 2024Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimizationcited by 1
  22. 2025Sample-Efficient Reinforcement Learning of Koopman eNMPCcited by 1
  23. 2025Bi-Level Reinforcement Learning Pathway for Sim-to-Real Optimalitycited by 1
  24. 2026Sharing the Control Authority Between Deep Reinforcement Learning and Model Predictive Control: Application to Multi-Class Transportation Networkscited by 1
  25. 2021Error-free approximation of explicit linear MPC through lattice piecewise affine expressioncited by 0
  26. 2022Bridging the gap between QP-based and MPC-based RLcited by 0
  27. 2022Performance-Driven Controller Tuning via Derivative-Free Reinforcement Learningcited by 0
  28. 2023Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Drivingcited by 0
  29. 2023Model predictive control-based value estimation for efficient reinforcement learningcited by 0
  30. 2024Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Overview and Perspectivescited by 0
  31. 2025Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundationscited by 0
  32. 2025Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agentscited by 0
  33. 2025Computationally efficient Gauss-Newton reinforcement learning for model predictive controlcited by 0
  34. 2025End-to-End Reinforcement Learning of Koopman Models for eNMPC of an Air Separation Unitcited by 0
  35. 2025Direct transfer of optimized controllers to similar systems using dimensionless MPCcited by 0
  36. 2026Impact of Markov Decision Process Design on Sim-to-Real Reinforcement Learningcited by 0
  37. 2026Soft MPCritic: Amortized Model Predictive Value Iterationcited by 0
  38. 2026A Systematic Review and Taxonomy of Reinforcement Learning-Model Predictive Control Integration for Linear Systemscited by 0

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