Abstract
This paper introduces the normalized and signed gradient dynamical systems associated with a differentiable function. Extending recent results on nonsmooth stability analysis, we characterize their asymptotic convergence properties and identify conditions that guarantee finite-time convergence. We discuss the application of the results to the design of multiagent coordination algorithms, paying special attention to their scalability properties. Finally, we consider network consensus problems and show how the proposed nonsmooth gradient flows achieve the desired coordination task in finite time.
Keywords
Convergence (economics)Differentiable functionScalabilityComputer scienceTask (project management)Exponential stabilityStability (learning theory)Mathematical optimizationFunction (biology)Applied mathematicsDynamical systems theoryControl theory (sociology)MathematicsArtificial intelligenceMathematical analysisControl (management)EngineeringMachine learning
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Publication Info
- Year
- 2006
- Type
- article
- Volume
- 173
- Pages
- 6376-6381
- Citations
- 27
- Access
- Closed
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Cite This
Jorge Cortés
(2006).
Achieving coordination tasks in finite time via nonsmooth gradient flows.
, 173
, 6376-6381.
https://doi.org/10.1109/cdc.2005.1583184
Identifiers
- DOI
- 10.1109/cdc.2005.1583184