Piecewise quadratic stability of fuzzy systems
- M. Johansson, A. Rantzer, Karl-Erik Årzén
- Computer ScienceIEEE transactions on fuzzy systems
- 1 December 1999
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.
Piecewise Linear Control Systems
- M. Johansson, M. Johanssn
- Mathematics, Computer Science
- 1 February 2003
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.
The Convergence of Sparsified Gradient Methods
- Dan Alistarh, T. Hoefler, M. Johansson, Sarit Khirirat, Nikola Konstantinov, Cédric Renggli
- Computer ScienceNeural Information Processing Systems
- 27 September 2018
It is proved that, under analytic assumptions, sparsifying gradients by magnitude with local error correction provides convergence guarantees, for both convex and non-convex smooth objectives, for data-parallel SGD.
Simultaneous routing and resource allocation via dual decomposition
- Lin Xiao, M. Johansson, Stephen P. Boyd
- Computer ScienceIEEE Transactions on Communications
- 1 July 2004
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.
Piecewise linear quadratic optimal control
- A. Rantzer, M. Johansson
- Computer Science, MathematicsProceedings of the American Control Conference…
- 4 June 1997
A technique for computation of piecewise quadratic Lyapunov functions is developed for performance analysis and controller synthesis for nonlinear systems based on convex optimization in terms of linear matrix inequalities.
Low power, low delay: Opportunistic routing meets duty cycling
- O. Landsiedel, E. Ghadimi, S. Duquennoy, M. Johansson
- Computer ScienceInternational Symposium on Information Processing…
- 16 April 2012
This paper introduces ORW, a practical opportunistic routing scheme for wireless sensor networks that reduces radio duty-cycles on average by 50% and delays by 30% to 90% when compared to the state of the art.
Optimal Parameter Selection for the Alternating Direction Method of Multipliers (ADMM): Quadratic Problems
- E. Ghadimi, André Teixeira, I. Shames, M. Johansson
- Computer ScienceIEEE Transactions on Automatic Control
- 11 June 2013
This paper finds the optimal algorithm parameters that minimize the convergence factor of the ADMM iterates in the context of ℓ2-regularized minimization and constrained quadratic programming.
Cross-layer optimization of wireless networks using nonlinear column generation
- M. Johansson, Lin Xiao
- Computer ScienceIEEE Transactions on Wireless Communications
- 1 November 2006
A specialized solution method is developed, based on a nonlinear column generation technique, and it is proved that it converges to the globally optimal solution.
Global convergence of the Heavy-ball method for convex optimization
- E. Ghadimi, H. Feyzmahdavian, M. Johansson
- MathematicsEuropean Control Conference
- 23 December 2014
This paper establishes global convergence and provides global bounds of the rate of convergence for the Heavy-ball method for convex optimization. When the objective function has Lipschitz-continuous…
Subgradient methods and consensus algorithms for solving convex optimization problems
- B. Johansson, T. Keviczky, M. Johansson, K. Johansson
- MathematicsIEEE Conference on Decision and Control
- 1 December 2008
This paper proposes a subgradient method for solving coupled optimization problems in a distributed way given restrictions on the communication topology and studies convergence properties of the proposed scheme using results from consensus theory and approximate subgradient methods.
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