Marcelo D. Fragoso

About

Marcelo D. Fragoso is a leading figure in stochastic control theory, best known for his pioneering work on **Markov jump linear systems (MJLS)**. His research focuses on the robust control, stability, and filtering of dynamic systems subject to abrupt changes in structure, modeled by Markov chains. Fragoso’s major contributions include the development of foundational frameworks for **continuous-time and discrete-time MJLS**, where he introduced novel operator-theoretic approaches to address mean square stability and guaranteed cost control. His landmark book, *Continuous-Time Markov Jump Linear Systems* (2012), has accumulated over **496 citations**, serving as a definitive reference in the field. In his highly cited 2015 work, he advanced robust \( H_2 \) and mixed \( H_2/H_\infty \) control for discrete-time MJLS by leveraging a set of four key operators, enabling new linear matrix inequality formulations. He also extended these results to infinite Markov jump parameters, addressing complex real-world scenarios. Fragoso’s work has profoundly impacted areas such as aerospace, networked control, and financial modeling, where systems must operate reliably under random structural changes. His rigorous theoretical contributions continue to inspire researchers and engineers tackling uncertainty in dynamic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Continuous-Time Markov Jump Linear Systems

   496 citations · 2012
2. 2
   A new look at the robust control of discrete-time Markov jump linear systems

   13 citations · 2015
3. 3
   On the state-feedback robust control of continuous-time infinite Markov jump linear systems

   8 citations · 2010
4. 4
   Some Numerical Examples

   2 citations · 2012

Key Collaborators

Contact & Links