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**Harvard**

Wik, T., Rutquist, P. och Breitholtz, C. (2010) *State-Constrained Control Based on Linearization of the Hamilton-Jacobi-Bellman Equation*.

** BibTeX **

@conference{

Wik2010,

author={Wik, Torsten and Rutquist, Per and Breitholtz, Claes},

title={State-Constrained Control Based on Linearization of the Hamilton-Jacobi-Bellman Equation},

booktitle={15th Nordic Process Control Workshop, Lund},

abstract={For continuous time, state constrained, stochastic
control problems a method based on optimization is presented. The method applies to systems where the control signal and the disturbance both enters affinely, and it has one main tuning paramater, which determines the control activity. If the disturbance covariance is unknown, it can also be used as a tuning parameter (matrix) to adjust the control directions in an intuitive way. Optimal control problems for this type of systems result in Hamilton Jacobi Bellman (HJB) equations that are problematic to solve because of nonlinearity and infinite boundary conditions. However, by applying a logarithmic transformation we show how and when the HJB equation can be transformed into a linear eigenvalue problem for which there are sometimes analytical solutions and if not, it can readily be solved with standard numerical methods. Sufficient and necessary conditions for when the method can be applied are derived, and their physical interpretation is discussed. A MIMO
buffer control problem is used as an illustration.},

year={2010},

keywords={Optimal control, HJB},

}

** RefWorks **

RT Conference Proceedings

SR Print

ID 134386

A1 Wik, Torsten

A1 Rutquist, Per

A1 Breitholtz, Claes

T1 State-Constrained Control Based on Linearization of the Hamilton-Jacobi-Bellman Equation

YR 2010

T2 15th Nordic Process Control Workshop, Lund

AB For continuous time, state constrained, stochastic
control problems a method based on optimization is presented. The method applies to systems where the control signal and the disturbance both enters affinely, and it has one main tuning paramater, which determines the control activity. If the disturbance covariance is unknown, it can also be used as a tuning parameter (matrix) to adjust the control directions in an intuitive way. Optimal control problems for this type of systems result in Hamilton Jacobi Bellman (HJB) equations that are problematic to solve because of nonlinearity and infinite boundary conditions. However, by applying a logarithmic transformation we show how and when the HJB equation can be transformed into a linear eigenvalue problem for which there are sometimes analytical solutions and if not, it can readily be solved with standard numerical methods. Sufficient and necessary conditions for when the method can be applied are derived, and their physical interpretation is discussed. A MIMO
buffer control problem is used as an illustration.

LA eng

OL 30