M
Mikael Johansson
Researcher at Royal Institute of Technology
Publications - 572
Citations - 20500
Mikael Johansson is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Convex optimization & Wireless network. The author has an hindex of 65, co-authored 526 publications receiving 18329 citations. Previous affiliations of Mikael Johansson include Helsinki University of Technology & Saarland University.
Papers
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Journal ArticleDOI
Computation of piecewise quadratic Lyapunov functions for hybrid systems
Mikael Johansson,Anders Rantzer +1 more
TL;DR: The search for a piecewise quadratic Lyapunov function is formulated as a convex optimization problem in terms of linear matrix inequalities and the relation to frequency domain methods such as the circle and Popov criteria is explained.
Journal Article
Computation of Piecewise Quadratic Lyapunov Functions for Hybrid Systems
Mikael Johansson,Anders Rantzer +1 more
TL;DR: In this paper, the search for a piecewise quadratic Lyapunov function is formulated as a convex optimization problem in terms of linear matrix inequalities, and the relation to frequency domain methods such as the circle and Popov criteria is explained.
Journal ArticleDOI
Piecewise quadratic stability of fuzzy systems
TL;DR: The approach exploits the gain-scheduling nature of fuzzy systems and results in stability conditions that can be verified via convex optimization over linear matrix inequalities, and special attention is given to the computational aspects of the approach.
Journal ArticleDOI
Simultaneous routing and resource allocation via dual decomposition
TL;DR: This paper forms the simultaneous routing and resource allocation (SRRA) problem as a convex optimization problem over the network flow variables and the communications variables, and exploits problem structure to derive efficient solution methods.
BookDOI
Piecewise Linear Control Systems
Mikael Johansson,M. Johanssn +1 more
TL;DR: This thesis treats analysis and design of piecewise linear control systems, and it is shown how Lyapunov functions with a discontinuous dependence on the discrete state can be computed via convex optimization.