What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Computer vision
His scientific interests lie mostly in Lyapunov function, Mathematical optimization, Polynomial, Control theory and Linear matrix inequality.
His Lyapunov function study which covers Linear system that intersects with Lyapunov optimization.
His research in the fields of Optimization problem overlaps with other disciplines such as Convex optimization.
His work deals with themes such as Domain, Domain and Polytope, which intersect with Polynomial.
His work in Control theory addresses subjects such as Visual servoing, which are connected to disciplines such as Trajectory and Motion planning.
His Linear matrix inequality research includes elements of Nonlinear control, Nonlinear system and Symmetric matrix.
His most cited work include:
- LMI Techniques for Optimization Over Polynomials in Control: A Survey (315 citations)
- Polynomially parameter-dependent Lyapunov functions for robust stability of polytopic systems: an LMI approach (232 citations)
- Brief Homogeneous Lyapunov functions for systems with structured uncertainties (167 citations)
What are the main themes of his work throughout his whole career to date?
Graziano Chesi mainly focuses on Lyapunov function, Mathematical optimization, Control theory, Polynomial and Linear matrix inequality.
The study incorporates disciplines such as Applied mathematics, Linear system and Homogeneous polynomial in addition to Lyapunov function.
His work on Optimization problem as part of general Mathematical optimization research is often related to Convex optimization, thus linking different fields of science.
Graziano Chesi focuses mostly in the field of Control theory, narrowing it down to matters related to Visual servoing and, in some cases, Field of view and Path.
His Polynomial study combines topics in areas such as Polytope, Control theory, Computation and Domain.
His work carried out in the field of Linear matrix inequality brings together such families of science as Stability, Representation, Essential matrix, Eigenvalues and eigenvectors and Symmetric matrix.
He most often published in these fields:
- Lyapunov function (36.89%)
- Mathematical optimization (33.61%)
- Control theory (32.38%)
What were the highlights of his more recent work (between 2016-2021)?
- Control theory (32.38%)
- Lyapunov function (36.89%)
- Linear system (16.80%)
In recent papers he was focusing on the following fields of study:
Graziano Chesi mostly deals with Control theory, Lyapunov function, Linear system, Symmetric matrix and Applied mathematics.
Control theory is often connected to Polynomial in his work.
His studies deal with areas such as Upper and lower bounds, Quadratic growth and Robustness as well as Lyapunov function.
His Robustness research integrates issues from Lyapunov redesign and Mathematical optimization.
His studies in Symmetric matrix integrate themes in fields like Linear matrix inequality, Eigenvalues and eigenvectors and Output feedback.
The various areas that Graziano Chesi examines in his Applied mathematics study include Discrete mathematics, Discrete time and continuous time, Linear quadratic and State-transition matrix.
Between 2016 and 2021, his most popular works were:
- Robust Stability Analysis and Synthesis for Uncertain Discrete-Time Networked Control Systems Over Fading Channels (43 citations)
- On the Complexity of SOS Programming and Applications in Control Systems (19 citations)
- Homogeneous Rational Lyapunov Functions for Performance Analysis of Switched Systems With Arbitrary Switching and Dwell Time Constraints (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Algebra
His main research concerns Control theory, Lyapunov function, Convex optimization, Symmetric matrix and Control system.
His Control theory study typically links adjacent topics like Multilinear map.
His Lyapunov function research also works with subjects such as
- Linear system which connect with Norm,
- Robustness that intertwine with fields like Mathematical optimization.
His research in Mathematical optimization intersects with topics in Homogeneous polynomial, Lyapunov redesign, Controller design and Linear matrix.
You can notice a mix of various disciplines of study, such as Control theory, Matrix, Stability and Polynomial, in his Convex optimization studies.
His Symmetric matrix study integrates concerns from other disciplines, such as Passivity, Linear matrix inequality, Directed graph, Output feedback and Applied mathematics.
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