2010
DOI: 10.1016/j.jfranklin.2009.10.008
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Maximum principle for optimal boundary control of the Kuramoto–Sivashinsky equation

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Cited by 13 publications
(8 citation statements)
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“…Under proper convexity assumption on state variable, it is proved thatthe maximum principle is also sufficient condition for the controls to be optimal . In [1][2][3][4][5][6][7], the systems under consideration include only one control function. Also, the necessary and sufficient conditions for optimality are given for a single hyperbolic differential equation without damping term subject to the homogeneous boundary conditions in onespace dimension.…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations
“…Under proper convexity assumption on state variable, it is proved thatthe maximum principle is also sufficient condition for the controls to be optimal . In [1][2][3][4][5][6][7], the systems under consideration include only one control function. Also, the necessary and sufficient conditions for optimality are given for a single hyperbolic differential equation without damping term subject to the homogeneous boundary conditions in onespace dimension.…”
Section: Resultsmentioning
confidence: 99%
“…Also, the necessary and sufficient conditions for optimality are given for a single hyperbolic differential equation without damping term subject to the homogeneous boundary conditions in onespace dimension. But, in the present paper, as an original contribution to literature, the necessary and sufficient optimality conditions obtained in [1][2][3][4][5][6][7] are generalized for a general class of damped hyperbolic equation involving damping and several control functions subject to nonhomogeneous boundary conditions in one space dimension.…”
Section: Resultsmentioning
confidence: 99%
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“…Nowadays, it is believed that this method is especially suited for dealing with optimal control problems with multiple inequality constraints, whereas it is exactly one of the difficulties in optimal control theory. Many other optimal control approaches share this weakness in this regard (see, e.g., Chan and Guo, 1989; Dmitruk and Osmolovskii, 2014; Girsanov, 1972; Isac and Khan, 2008; Osmolovskii, 2018; Pedregal, 2017; Sun, 2010). Even for optimal control problems with time delay, there are also many successful examples that utilize the Dubovitskii–Milyutin method, such as that presented by Kotarski (1997).…”
Section: Fixed Final Time Horizon Casementioning
confidence: 99%