Dynamic event‐triggered communication based distributed optimization
Zhiqiang Zhang, Jan Lunze, Yuangong Sun, Zehuan Lu
Abstract
Abstract This article presents distributed continuous‐time algorithms with dynamic event‐triggered communication, called the dynamic event‐triggered algorithms, to solve a convex optimization problem in a multiagent network. Firstly, a new dynamic event‐triggered communication scheme is introduced and it is shown that the optimization problem is solved and occurrence of Zeno behavior is prevented. Secondly, under the dynamic event‐triggered communication implementations, both uniform and logarithmic quantized information algorithms are given to solve the optimization problem. Finally, numerical simulations are given to illustrate the effectiveness of the derived results.
Topics & Concepts
Computer scienceLogarithmOptimization problemScheme (mathematics)Event (particle physics)Convex optimizationImplementationMathematical optimizationZeno's paradoxesRegular polygonDistributed computingAlgorithmMathematicsPhysicsMathematical analysisQuantum mechanicsGeometryProgramming languageDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationMathematical and Theoretical Epidemiology and Ecology Models