Search Results for author: Teodoro Alamo

Found 10 papers, 0 papers with code

Tractable robust MPC design based on nominal predictions

no code implementations13 Apr 2021 Ignacio Alvarado, Pablo Krupa, Daniel Limon, Teodoro Alamo

Many popular approaches in the field of robust model predictive control (MPC) are based on nominal predictions.

Real-time implementation of MPC for tracking in embedded systems: Application to a two-wheeled inverted pendulum

no code implementations26 Mar 2021 Pablo Krupa, Jose Camara, Ignacio Alvarado, Daniel Limon, Teodoro Alamo

This article presents the real-time implementation of the model predictive control for tracking formulation to control a two-wheeled inverted pendulum robot.

Restart of accelerated first order methods with linear convergence under a quadratic functional growth condition

no code implementations24 Feb 2021 Teodoro Alamo, Pablo Krupa, Daniel Limon

Accelerated first order methods, also called fast gradient methods, are popular optimization methods in the field of convex optimization.

Optimization and Control

Chance constrained sets approximation: A probabilistic scaling approach -- EXTENDED VERSION

no code implementations15 Jan 2021 Martina Mammarella, Victor Mirasierra, Matthias Lorenzen, Teodoro Alamo, Fabrizio Dabbene

In this paper, a sample-based procedure for obtaining simple and computable approximations of chance-constrained sets is proposed.

Probabilistic interval predictor based on dissimilarity functions

no code implementations29 Oct 2020 A. Daniel Carnerero, Daniel R. Ramirez, Teodoro Alamo

The method relies on the use of dissimilarity functions to estimate the conditional probability density function of the outputs.

Implementation of model predictive control for tracking in embedded systems using a sparse extended ADMM algorithm

no code implementations20 Aug 2020 Pablo Krupa, Ignacio Alvarado, Daniel Limon, Teodoro Alamo

This article presents a sparse, low-memory footprint optimization algorithm for the implementation of the model predictive control (MPC) for tracking formulation in embedded systems.

Open Data Resources for Fighting COVID-19

no code implementations13 Apr 2020 Teodoro Alamo, Daniel G. Reina, Martina Mammarella, Alberto Abella

In an attempt to facilitate the rapid response to the study of the seasonal behaviour of Covid-19, we enumerate the main open resources in terms of weather and climate variables.

Probabilistic performance validation of deep learning-based robust NMPC controllers

no code implementations30 Oct 2019 Benjamin Karg, Teodoro Alamo, Sergio Lucia

Solving nonlinear model predictive control problems in real time is still an important challenge despite of recent advances in computing hardware, optimization algorithms and tailored implementations.

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