Daniel Limón
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View article: Robust tracking MPC for perturbed nonlinear systems -- Extended version
Robust tracking MPC for perturbed nonlinear systems -- Extended version Open
This paper presents a novel robust predictive controller for constrained nonlinear systems that is able to track piece-wise constant setpoint signals. The tracking model predictive controller presented in this paper extends the nonlinear M…
View article: Robust contraction-based model predictive control for nonlinear systems
Robust contraction-based model predictive control for nonlinear systems Open
Model Predictive Control (MPC) is a widely known control method that has proved to be particularly effective in multivariable and constrained control. Closed-loop stability and recursive feasibility can be guaranteed by employing accurate …
View article: Economic Model Predictive Control for Periodic Operation: A Quadratic Programming Approach
Economic Model Predictive Control for Periodic Operation: A Quadratic Programming Approach Open
Periodic dynamical systems, distinguished by their repetitive behavior over time, are prevalent across various engineering disciplines. In numerous applications, particularly within industrial contexts, the implementation of model predicti…
View article: Model Predictive Control for Tracking Using Artificial References: Fundamentals, Recent Results and Practical Implementation
Model Predictive Control for Tracking Using Artificial References: Fundamentals, Recent Results and Practical Implementation Open
Slides of the tutorial session "Model Predictive Control for Tracking Using Artificial References: Fundamentals, Recent Results and Practical Implementation", presented in the 63rd IEEE Conference on Decision and Control, Milano, Italy.
View article: Designing Implicit Invariant Sets for Model Predictive Control for Tracking
Designing Implicit Invariant Sets for Model Predictive Control for Tracking Open
This work introduces a model predictive control (MPC) approach designed for tracking changing setpoints with implicit terminal components. In the presented method, an artificial setpoint is used as a decision variable, and the terminal con…
View article: Economic model predictive control for periodic operation: a quadratic programming approach
Economic model predictive control for periodic operation: a quadratic programming approach Open
Periodic dynamical systems, distinguished by their repetitive behavior over time, are prevalent across various engineering disciplines. In numerous applications, particularly within industrial contexts, the implementation of model predicti…
View article: Efficient Implementation of MPC for Tracking using ADMM by Decoupling its Semi-Banded Structure
Efficient Implementation of MPC for Tracking using ADMM by Decoupling its Semi-Banded Structure Open
Accepted version of the article published in IEEE European Control Conference
View article: Recent advancements on MPC for tracking: periodic and harmonic formulations
Recent advancements on MPC for tracking: periodic and harmonic formulations Open
The main benefit of model predictive control (MPC) is its ability to steer the system to a given reference without violating the constraints while minimizing some objective. Furthermore, a suitably designed MPC controller guarantees asympt…
View article: A Sparse ADMM-Based Solver for Linear MPC Subject to Terminal Quadratic Constraint
A Sparse ADMM-Based Solver for Linear MPC Subject to Terminal Quadratic Constraint Open
Model Predictive Control (MPC) typically includes a terminal constraint to guarantee stability of the closed-loop system under nominal conditions. In linear MPC this constraint is generally taken on a polyhedral set, leading to a quadratic…
View article: MPC for Tracking applied to rendezvous with non-cooperative tumbling targets ensuring stability and feasibility
MPC for Tracking applied to rendezvous with non-cooperative tumbling targets ensuring stability and feasibility Open
A Model Predictive Controller for Tracking is introduced for rendezvous with non-cooperative tumbling targets in active debris removal applications. The target's three-dimensional non-periodic rotational dynamics as well as other state and…
View article: Model Predictive Control for setpoint tracking
Model Predictive Control for setpoint tracking Open
The main objective of tracking control is to steer the tracking error, that is the difference between the reference and the output, to zero while the plant's operation limits are satisfied. This requires that some assumptions on the evolut…
View article: Efficient implementation of MPC for tracking using ADMM by decoupling its semi-banded structure
Efficient implementation of MPC for tracking using ADMM by decoupling its semi-banded structure Open
Model Predictive Control (MPC) for tracking formulation presents numerous advantages compared to standard MPC, such as a larger domain of attraction and recursive feasibility even when abrupt changes in the reference are produced. As a dra…
View article: Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways
Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways Open
In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling these uncertainties, …
View article: Efficient management of HVAC systems through coordinated operation of parallel chiller units: An economic predictive control approach
Efficient management of HVAC systems through coordinated operation of parallel chiller units: An economic predictive control approach Open
In developed countries, air conditioning systems have become major contributors to energy consumption in buildings. Cooling installations made up of independent chiller units connected in parallel pose a challenge in finding the most energ…
View article: Implementation of Soft-Constrained MPC for Tracking Using Its Semi-Banded Problem Structure
Implementation of Soft-Constrained MPC for Tracking Using Its Semi-Banded Problem Structure Open
Model Predictive Control (MPC) is a popular control approach due to its\nability to consider constraints, including input and state restrictions, while\nminimizing a cost function. However, in practice, these constraints can result\nin fea…
View article: Harmonic model predictive control for tracking sinusoidal references and its application to trajectory tracking
Harmonic model predictive control for tracking sinusoidal references and its application to trajectory tracking Open
Harmonic model predictive control (HMPC) is a recent model predictive control (MPC) formulation for tracking piece-wise constant references that includes a parameterized artificial harmonic reference as a decision variable, resulting in an…
View article: Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways
Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways Open
In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling these uncertainties, …
View article: Modifier-Adaptation for Real-Time Optimal Periodic Operation
Modifier-Adaptation for Real-Time Optimal Periodic Operation Open
In this paper, we present the periodic modifier-adaptation formulation of the dynamic real time optimization. The proposed formulation uses gradient information to update the problem with affine modifiers so that, upon convergence, its sol…
View article: Efficient online update of model predictive control in embedded systems using first-order methods
Efficient online update of model predictive control in embedded systems using first-order methods Open
Model Predictive Control (MPC) is typically characterized for being computationally demanding, as it requires solving optimization problems online; a particularly relevant point when considering its implementation in embedded systems. To r…
View article: Efficiently Solving the Harmonic Model Predictive Control Formulation
Efficiently Solving the Harmonic Model Predictive Control Formulation Open
Harmonic model predictive control (HMPC) is a model predictive control (MPC) formulation that displays several benefits over other MPC formulations, especially when using a small prediction horizon. These benefits, however, come at the exp…
View article: Thermal modeling of existing buildings in high-fidelity simulators: A novel, practical methodology
Thermal modeling of existing buildings in high-fidelity simulators: A novel, practical methodology Open
Optimizing efficiency in the operation of the HVAC system of existing buildings requires the construction of a thermal dynamic model of the building, which may be challenging because architectural metadata may be missing or obsolete. Based…
View article: Kernel-Based State-Space Kriging for Predictive Control
Kernel-Based State-Space Kriging for Predictive Control Open
A preliminary version of this paper was presented at the 2022 IEEE Conference on Decision and Control
View article: Computation of maximal output admissible sets for linear systems with polynomial constraints
Computation of maximal output admissible sets for linear systems with polynomial constraints Open
In this technical note we study the computation of the Maximal Output Admissible Set for linear systems subject to polynomial constraints. The computation of an inner approximation of the Maximal Output Admissible Sets requires the determi…
View article: Learning-based NMPC on SoC platforms for real-time applications using parallel Lipschitz interpolation
Learning-based NMPC on SoC platforms for real-time applications using parallel Lipschitz interpolation Open
One of the main problems associated with advanced control strategies is their implementation on embedded and industrial platforms, especially when the target application requires real-time operation. Frequently, the dynamics of the system …
View article: Efficient Online Update of Model Predictive Control in Embedded Systems Using First-Order Methods
Efficient Online Update of Model Predictive Control in Embedded Systems Using First-Order Methods Open
Model Predictive Control (MPC) is typically characterized for being computationally demanding, as it requires solving optimization problems online; a particularly relevant point when considering its implementation in embedded systems. To r…