IPA for continuous stochastic marked graphs

DOI10.1016/j.automatica.2013.02.006zbMath1319.93073OpenAlexW2084314065MaRDI QIDQ490547

Carla Seatzu, Alessandro Giua, Yoraï Wardi

Publication date: 27 August 2015

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2013.02.006

zbMATH Keywords

infinitesimal perturbation analysisstochastic hybrid systemsmarked graphscontinuous Petri nets

Mathematics Subject Classification ID

Perturbations in control/observation systems (93C73) Discrete event control/observation systems (93C65) Stochastic systems in control theory (general) (93E03)

Related Items (5)

Individuals, populations and fluid approximations: a Petri net based perspective ⋮ Performance regulation of event-driven dynamical systems using infinitesimal perturbation analysis ⋮ Impact of the Corrective Maintenance Cost on Manufacturing Remanufacturing System Performance ⋮ IPA for continuous stochastic marked graphs ⋮ Dynamics and steady state analysis of controlled generalized batches Petri nets

Uses Software

• UMDES

Cites Work

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• IPA for continuous stochastic marked graphs
• Perturbation analysis and optimization of multiclass multiobjective stochastic flow models
• Perturbation analysis and optimization of stochastic hybrid systems
• Optimal scheduling of parallel queues using stochastic flow models
• Infinitesimal perturbation analysis and optimization for make-to-stock manufacturing systems based on stochastic fluid models
• Stochastic approximation methods for constrained and unconstrained systems
• Online IPA gradient estimators in stochastic continuous fluid models
• Derivative estimation for buffer capacity of continuous transfer lines subject to operation-dependent failures
• Discrete, Continuous, and Hybrid Petri Nets
• A Unified Approach to Infinitesimal Perturbation Analysis in Stochastic Flow Models: The Single-Stage Case
• Perturbation analysis for online control and optimization of stochastic fluid models
• IPA Derivatives for Make-to-Stock Production-Inventory Systems With Lost Sales

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