4 citations · 5 across the 6 of their papers we have counts for
6 papers
Optimality Conditions for Model Predictive Control: Rethinking Predictive Model Design
Akhil S Anand, Arash Bahari Kordabad, Mario Zanon +1
Optimality is a critical aspect of Model Predictive Control (MPC), especially in economic MPC. However, achieving optimality in MPC presents significant challenges, and may even be…
Economic Model Predictive Control as a Solution to Markov Decision Processes
Dirk Reinhardt, Akhil S. Anand, Shambhuraj Sawant +1
Markov Decision Processes (MDPs) offer a fairly generic and powerful framework to discuss the notion of optimal policies for dynamic systems, in particular when the dynamics are st…
Personalized Dynamic Pricing Policy for Electric Vehicles: Reinforcement learning approach
Sangjun Bae, Balazs Kulcsar, Sebastien Gros
With the increasing number of fast-electric vehicle charging stations (fast-EVCSs) and the popularization of information technology, electricity price competition between fast-EVCS…
Integrated Charging Scheduling and Operational Control for an Electric Bus Network
Rémi Lacombe, Nikolce Murgovski, Sébastien Gros +1
The last few years have seen the massive deployment of electric buses in many existing transit networks. However, the planning and operation of an electric bus system differ from t…
Once upon a time step: A closed-loop approach to robust MPC design
Anilkumar Parsi, Marcell Bartos, Amber Srivastava +2
A novel perspective on the design of robust model predictive control (MPC) methods is presented, whereby closed-loop constraint satisfaction is ensured using recursive feasibility…
Deep active learning for nonlinear system identification
Erlend Torje Berg Lundby, Adil Rasheed, Ivar Johan Halvorsen +3
The exploding research interest for neural networks in modeling nonlinear dynamical systems is largely explained by the networks' capacity to model complex input-output relations d…