@article{(Open Science Index):https://publications.waset.org/pdf/10002375,
	  title     = {Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution},
	  author    = {Tomoaki Hashimoto},
	  country	= {},
	  institution	= {},
	  abstract     = {In recent decades, probabilistic constrained optimal
control problems have attracted much attention in many research
fields. Although probabilistic constraints are generally intractable
in an optimization problem, several tractable methods haven been
proposed to handle probabilistic constraints. In most methods,
probabilistic constraints are reduced to deterministic constraints
that are tractable in an optimization problem. However, there is a
gap between the transformed deterministic constraints in case of
known and unknown probability distribution. This paper examines
the conservativeness of probabilistic constrained optimization method
for unknown probability distribution. The objective of this paper is
to provide a quantitative assessment of the conservatism for tractable
constraints in probabilistic constrained optimization with unknown
probability distribution.},
	    journal   = {International Journal of Physical and Mathematical Sciences},
	  volume    = {9},
	  number    = {9},
	  year      = {2015},
	  pages     = {534 - 538},
	  ee        = {https://publications.waset.org/pdf/10002375},
	  url   	= {https://publications.waset.org/vol/105},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 105, 2015},
	}