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Robust control is a core approach for controlling systems with performance guarantees that are robust to modeling error, and is widely used in real-world systems. However, current robust control approaches can only handle small system…

Optimization and Control · Mathematics 2021-06-08 Dimitar Ho , Hoang M. Le , John C. Doyle , Yisong Yue

In this paper, we present Robust Model Predictive Control (MPC) problems with adjustable uncertainty sets. In contrast to standard Robust MPC problems with known uncertainty sets, we treat the uncertainty sets in our problems as additional…

Optimization and Control · Mathematics 2018-09-21 Yeojun Kim , Xiaojing Zhang , Jacopo Guanetti , Francesco Borrelli

This paper deals with the stochastic control of nonlinear systems in the presence of state and control constraints, for uncertain discrete-time dynamics in finite dimensional spaces. In the deterministic case, the viability kernel is known…

Optimization and Control · Mathematics 2010-02-08 Luc Doyen , Delara Michel

It is estimated that around 80\% of the world's population live in areas susceptible to at-least one major vector borne disease, and approximately 20% of global communicable diseases are spread by mosquitoes. Furthermore, the outbreaks of…

According to the World Health Organization, dengue fever is the most important mosquito-borne disease of humans, and it is currently estimated that there may be 50 - 100 million yearly dengue infections worldwide. For the purpose to provide…

Populations and Evolution · Quantitative Biology 2016-08-10 L. S. Barsante , K. S. Paixão , K. H. Laass , R. T. N. Cardoso , Á. E. Eiras , J. L. Acebal

Dengue remains a major global public health concern due to its high mortality and economic burden. Mathematical modeling is essential to understand its transmission mechanisms and for evaluating intervention strategies. In this paper, we…

Populations and Evolution · Quantitative Biology 2026-04-28 Sourav Banerjee , Thomas Götz , Satyananda Panda

Distributionally robust control is a well-studied framework for optimal decision making under uncertainty, with the objective of minimizing an expected cost function over control actions, assuming the most adverse probability distribution…

Systems and Control · Electrical Eng. & Systems 2025-08-12 Alexandros E. Tzikas , Lukas Fiechtner , Arec Jamgochian , Mykel J. Kochenderfer

The incidence of Dengue epidemiologic disease has grown in recent decades. In this paper an application of optimal control in Dengue epidemics is presented. The mathematical model includes the dynamic of Dengue mosquito, the affected…

Optimization and Control · Mathematics 2010-09-03 Helena Sofia Rodrigues , M. Teresa T. Monteiro , Delfim F. M. Torres

Some monospecies age class models, as well as specific multi-species models (with so-called technical interactions), exhibit useful monotonicity properties. This paper deals with discrete time monotone bioeconomics dynamics in the presence…

Optimization and Control · Mathematics 2019-04-22 Michel De Lara , Pedro Gajardo , Hector Ramirez Cabrera

During the last decades, the global prevalence of dengue progressed dramatically. It is a disease which is now endemic in more than one hundred countries of Africa, America, Asia and the Western Pacific. This study addresses a mathematical…

Epidemiological models may give some basic guidelines for public health practitioners, allowing to analyze issues that can influence the strategies to prevent and fight a disease. To be used in decision-making, however, a mathematical model…

Populations and Evolution · Quantitative Biology 2013-08-15 Helena Sofia Rodrigues , M. Teresa T. Monteiro , Delfim F. M. Torres

This paper proposes a novel robust Model Predictive Control (MPC) scheme for linear discrete-time systems affected by model uncertainty described by interval matrices. The key feature of the proposed method is a bound on the uncertainty…

Systems and Control · Electrical Eng. & Systems 2026-02-20 Renato Quartullo , Andrea Garulli , Mirko Leomanni

Artificial releases of Wolbachia-infected Aedes mosquitoes have been under study in the past years for fighting vector-borne diseases such as dengue, chikungunya and zika. Several strains of this bacterium cause cytoplasmic incompatibility…

Analysis of PDEs · Mathematics 2017-07-31 Martin Strugarek , Nicolas Vauchelet , Jorge Zubelli

Ross-Macdonald models are the building blocks of most vector-borne disease models. Even for the same disease, different authors use different model formulations, but a study of the dynamical consequences of assuming different hypotheses is…

Populations and Evolution · Quantitative Biology 2020-07-22 Mario Ignacio Simoy , Juan Pablo Aparicio

Robust model predictive control algorithms are essential for addressing unavoidable errors due to the uncertainty in predicting real-world systems. However, the formulation of such algorithms typically results in a trade-off between…

Systems and Control · Electrical Eng. & Systems 2025-04-25 Moritz Heinlein , Sankaranarayanan Subramanian , Sergio Lucia

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to…

Dengue continues to pose a major global threat, infecting nearly 390 million people annually. Recognizing the pivotal role of vector competence (vc), recent research focuses on mosquito parameters to inform transmission modeling and vector…

Populations and Evolution · Quantitative Biology 2025-11-07 Piyumi Chathurangika , Tharushika Peiris , Lakmini S. Premadasa , S. S. N. Perera , Kushani De Silva

Mosquito vector competence is usually represented as a process in which once virus is detected in saliva, mosquitoes are assumed to remain infectious for life, implying an irreversible transition to the transmitting state. However, some…

Populations and Evolution · Quantitative Biology 2026-04-30 Léa Loisel , Tristan Monrocq , Vincent Raquin , Pauline Ezanno , Gaël Beaunée

Robust Optimal Control (ROC) with adjustable uncertainties has proven to be effective in addressing critical challenges within modern energy networks, especially the reserve and provision problem. However, prior research on ROC with…

Systems and Control · Electrical Eng. & Systems 2023-12-19 Yun Li , Neil Yorke-Smith , Tamas Keviczky

According to recent results, convergence in a prespecified or prescribed finite time can be achieved under extreme model uncertainty if control is applied continuously over time. This paper shows that this extreme amount of uncertainty…

Systems and Control · Electrical Eng. & Systems 2023-06-27 Hernan Haimovich , Rodrigo Aldana-Lopez , Richard Seeber , David Gomez-Gutierrez