5 papers
Data-Driven Strategies for Hierarchical Predictive Control in Unknown Environments
Charlott Vallon, Francesco Borrelli
This article proposes a hierarchical learning architecture for safe data-driven control in unknown environments. We consider a constrained nonlinear dynamical system and assume the…
Task Decomposition for MPC: A Computationally Efficient Approach for Linear Time-Varying Systems
Charlott Vallon, Francesco Borrelli
A Task Decomposition method for iterative learning Model Predictive Control (TDMPC) for linear time-varying systems is presented. We consider the availability of state-input trajec…
Data-Driven Hierarchical Predictive Learning in Unknown Environments
Charlott Vallon, Francesco Borrelli
We propose a hierarchical learning architecture for predictive control in unknown environments. We consider a constrained nonlinear dynamical system and assume the availability of…
Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint
Monimoy Bujarbaruah, Charlott Vallon
This paper proposes an Adaptive Stochastic Model Predictive Control (MPC) strategy for stable linear time-invariant systems in the presence of bounded disturbances. We consider mul…
Task Decomposition for Iterative Learning Model Predictive Control
Charlott Vallon, Francesco Borrelli
A task decomposition method for iterative learning model predictive control is presented. We consider a constrained nonlinear dynamical system and assume the availability of state-…