1.2k citations · 1.7k across the 52 of their papers we have counts for
15 papers · 1 filter
Harmonic model predictive control for tracking sinusoidal references and its application to trajectory tracking
Pablo Krupa, Daniel Limon, Alberto Bemporad +1
Harmonic model predictive control (HMPC) is a recent model predictive control (MPC) formulation for tracking piece-wise constant references that includes a parameterized artificial…
Data-Driven Synthesis of Configuration-Constrained Robust Invariant Sets for Linear Parameter-Varying Systems
Manas Mejari, Sampath Kumar Mulagaleti, Alberto Bemporad
We present a data-driven method to synthesize robust control invariant (RCI) sets for linear parameter-varying (LPV) systems subject to unknown but bounded disturbances. A finite-l…
Computation of safe disturbance sets using implicit RPI sets
Sampath Kumar Mulagaleti, Alberto Bemporad, Mario Zanon
Given a stable linear time-invariant (LTI) system subject to output constraints, we present a method to compute a set of disturbances such that the reachable set of outputs matches…
Parameter Dependent Robust Control Invariant Sets for LPV Systems with Bounded Parameter Variation Rate
Sampath Kumar Mulagaleti, Manas Mejari, Alberto Bemporad
Real-time measurements of the scheduling parameter of linear parameter-varying (LPV) systems enables the synthesis of robust control invariant (RCI) sets and parameter dependent co…
Counter-example guided inductive synthesis of control Lyapunov functions for uncertain systems
Daniele Masti, Filippo Fabiani, Giorgio Gnecco +1
We propose a counter-example guided inductive synthesis (CEGIS) scheme for the design of control Lyapunov functions and associated state-feedback controllers for linear systems aff…
An active learning method for solving competitive multi-agent decision-making and control problems
Filippo Fabiani, Alberto Bemporad
To identify a stationary action profile for a population of competitive agents, each executing private strategies, we introduce a novel active-learning scheme where a centralized e…
Learning Critical Scenarios in Feedback Control Systems for Automated Driving
Mengjia Zhu, Alberto Bemporad, Maximilian Kneissl +1
Testing is essential for verifying and validating control designs, especially in safety-critical applications. In particular, the control system governing an automated driving vehi…
Data-driven synthesis of Robust Invariant Sets and Controllers
Sampath Kumar Mulagaleti, Alberto Bemporad, Mario Zanon
This paper presents a method to identify an uncertain linear time-invariant (LTI) prediction model for tube-based Robust Model Predictive Control (RMPC). The uncertain model is det…
Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?
Sebastien Gros, Mario Zanon, Alberto Bemporad
For all its successes, Reinforcement Learning (RL) still struggles to deliver formal guarantees on the closed-loop behavior of the learned policy. Among other things, guaranteeing…
Constrained Controller and Observer Design by Inverse Optimality
Mario Zanon, Alberto Bemporad
Model Predictive Control (MPC) is often tuned by trial and error. When a baseline linear controller exists that is already well tuned in the absence of constraints and MPC is intro…
Efficient Calibration of Embedded MPC
Marco Forgione, Dario Piga, Alberto Bemporad
Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challe…
Practical Reinforcement Learning of Stabilizing Economic MPC
Mario Zanon, Sébastien Gros, Alberto Bemporad
Reinforcement Learning (RL) has demonstrated a huge potential in learning optimal policies without any prior knowledge of the process to be controlled. Model Predictive Control (MP…
Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected vehicle prognostics
Valentina Breschi, Ilya Kolmanovsky, Alberto Bemporad
As the connectivity of consumer devices is rapidly growing and cloud computing technologies are becoming more widespread, cloud-aided techniques for parameter estimation can be des…
Trajectory Planning Under Vehicle Dimension Constraints Using Sequential Linear Programming
Mogens Graf Plessen, Pedro F. Lima, Jonas Martensson +2
This paper presents a spatial-based trajectory planning method for automated vehicles under actuator, obstacle avoidance, and vehicle dimension constraints. Starting from a nonline…
A Convex Feasibility Approach to Anytime Model Predictive Control
Alberto Bemporad, Daniele Bernardini, Panagiotis Patrinos
This paper proposes to decouple performance optimization and enforcement of asymptotic convergence in Model Predictive Control (MPC) so that convergence to a given terminal set is…