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20242026
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eess.SY2026

Sharing the Control Authority Between Deep Reinforcement Learning and Model Predictive Control: Application to Multi-Class Transportation Networks

Giray Onur, Azita Dabiri, Bart De Schutter

Transportation networks, in particular multi-class transportation networks (i.e., networks with mixed vehicle types), are complex systems that are challenging to control. Recently,…

eess.SY2026

Model Predictive Control and Moving Horizon Estimation using Statistically Weighted Data-Based Ensemble Models

Laura Boca de Giuli, Samuel Mallick, Alessio La Bella +3

This paper presents a model predictive control (MPC) framework leveraging an ensemble of data-based models to optimally control complex systems under multiple operating conditions.…

eess.SY2026

Second-Order MPC-Based Distributed Q-Learning

Samuel Mallick, Filippo Airaldi, Azita Dabiri +1

The state of the art for model predictive control (MPC)-based distributed Q-learning is limited to first-order gradient updates of the MPC parameterization. In general, using secon…

eess.SY2026

Approximate Model Predictive Control for Microgrid Energy Management via Imitation Learning

Changrui Liu, Shengling Shi, Anil Alan +2

Efficient energy management is essential for reliable and sustainable microgrid operation amid increasing renewable integration. In this paper, an imitation learning-based framewor…

eess.SY2026

Temporal Logic Control of Nonlinear Stochastic Systems with Online Performance Optimization

Alessandro Riccardi, Thom Badings, Luca Laurenti +2

The deployment of autonomous systems in safety-critical environments requires control policies that guarantee satisfaction of complex control specifications. These systems are comm…

eess.SY2026

Integrated Online Monitoring and Adaptation of Process Model Predictive Controllers

Samuel Mallick, Laura Boca de de Giuli, Alessio La Bella +3

This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy s…