A stochastic minimum principle and an adaptive pathwise algorithm for stochastic optimal control

DOI10.1016/j.automatica.2013.02.053zbMath1360.93783OpenAlexW2158399406MaRDI QIDQ522803

Panos Parpas, Mort Webster

Publication date: 19 April 2017

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1721.1/99483

zbMATH Keywords

stochastic controlMonte Carlo simulationelectric power systems

Mathematics Subject Classification ID

Related Items (4)

On the information-based complexity of stochastic programming ⋮ Gradient iterative algorithm for dual-rate nonlinear systems based on a novel particle filter ⋮ A stochastic multiscale model for electricity generation capacity expansion ⋮ Multiobjective control for nonlinear stochastic Poisson jump-diffusion systems via T-S fuzzy interpolation and Pareto optimal scheme

Uses Software

• Matlab

Cites Work

• Applied stochastic control of jump diffusions.
• Convergence of the Euler--Maruyama method for stochastic differential equations with Markovian switching.
• Uncertainty in the electric power industry. Methods and models for decision support
• A stochastic multiscale model for electricity generation capacity expansion
• Turnpike properties for a class of piecewise deterministic systems arising in manufacturing flow control
• Particle methods for stochastic optimal control problems
• Computational Assessment of Nested Benders and Augmented Lagrangian Decomposition for Mean-Variance Multistage Stochastic Problems
• Stochastic Control in Discrete and Continuous Time
• Control of systems with jump Markov disturbances
• Introduction to Stochastic Programming
• Approximate Dynamic Programming
• Scattered Data Approximation
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