Results 161 to 170 of about 702 (187)

HJB Equations Through Backward Stochastic Differential Equations

2017
This last chapter of the book completes the picture of the main methods used to study second-order HJB equations in Hilbert spaces and related optimal control problems by presenting a survey of results that can be achieved with the techniques of Backward SDEs in infinite dimension.
Fuhrman, M, Tessitore, G.
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Markov chain approximation methods on generalized HJB equation

2007 46th IEEE Conference on Decision and Control, 2007
This work is concerned with numerical methods for a class of stochastic control optimizations and stochastic differential games. Numerical procedures based on Markov chain approximation techniques are developed in a framework of generalized Hamilton-Jacobi-Bellman equations.
Xueping Li 0002, Q. S. Song
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HJB equation based learning scheme for neural networks

2017 International Joint Conference on Neural Networks (IJCNN), 2017
A control theoretic approach is presented in this paper for both batch and instantaneous updates of weights in feed-forward neural networks. The popular Hamilton-Jacobi-Bellman (HJB) equation has been used to generate an optimal weight update law. The main contribution in this paper is that a closed form solutions for both optimal cost and weight ...
Vipul Arora 0001, Laxmidhar Behera, Tharun Kumar Reddy, Ajay Pratap Yadav   +3 more
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Ergodic Control for Constrained Diffusions: Characterization Using HJB Equations

SIAM Journal on Control and Optimization, 2004
Summary: Recently in [A. Budhiraja, SIAM J. Control Optim. 42, No. 2, 532--558 (2003; Zbl 1037.93073)] an ergodic control problem for a class of diffusion processes, constrained to take values in a polyhedral cone, was considered. The main result of that paper was that under appropriate conditions on the model, there is a Markov control for which the ...
Vivek S. Borkar, Amarjit Budhiraja
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Hamiltonian systems, HJB equations, and stochastic controls

Proceedings of the 36th IEEE Conference on Decision and Control, 2002
Pontraygin's maximum principle (MP) involving the Hamiltonian system and Bellman's dynamic programming (DP) involving the HJB equation are the two most important approaches in modern optimal control theory. However, these two approaches have been developed separately in literature and it has been a long-standing, yet fundamentally important problem to ...
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Viscosity Solutions of HJB Equations with Unbounded Data and Characteristic Points

Applied Mathematics and Optimization, 2003
The author refines and extends to the ``unbounded case'' certain previous results concerning viscosity-type properties of the value functions of optimal control problems which consist in the minimization of functionals of the form \[ J(t,x,\alpha(.)):=\int_0^t e^{-\int_0^tk(y(\sigma),\alpha(\sigma)) \,d\sigma} l((y(s),\alpha(s))ds+ e^{-\int_0^tk(y ...
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Optimal soot blowing and repair plan for boiler based on HJB equation

Optimization, 2022
Yuanhao Shi, Jianfang Jia, Jie Wen
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The HJB Equation for Deterministic Control

2008
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An iterative algorithm for solving a kind of discrete HJB equation with M-functions

Applied Mathematics Letters, 2011
Shuilian Xie, Hongru Xu
exaly  

Solution to the HJB equation for LQR-type problems on compact connected Lie groups

Automatica, 2018
Ilya Kolmanovsky, Anthony Bloch, Rohit Gupta   +2 more
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