39 lines
1.6 KiB
Mathematica
39 lines
1.6 KiB
Mathematica
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function varargout = robustmodel(varargin)
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%ROBUSTMODEL Derives robust counterpart.
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%
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% [Frobust,objrobust,failure] = ROBUSTMODEL(F,h,options) is used to derive
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% the robust counterpart of an uncertain YALMIP model.
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%
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% min h(x,w)
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% subject to
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% F(x,w) >(=) 0 for all w in W
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%
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% The constraints and objective have to satisfy a number of conditions for
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% the robustification to be possible. Please refer to the YALMIP Wiki for
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% the current assumptions.
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%
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% Some options for the robustification strategies can be altered via the
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% solver tag 'robust' in sdpsettings
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%
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% 'robust.lplp' : Controls how linear constraints with affine
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% parameterization in an uncertainty with polytopic
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% description is handled. Can be either 'duality' or
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% 'enumeration'
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%
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% 'robust.auxred': Controls how uncertainty dependent auxiliary variables
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% are handled
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% Can be either 'projection' or 'enumeration' (exact),
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% or 'none' or 'affine' (conservative)
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%
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% 'robust.reducedual' Controls if the system equality constraints derived
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% when using the duality filter should be eliminated,
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% thus reducing the number of variables, possibly
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% destroying sparsity .
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%
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% 'robust.polya' : Controls the relaxation order of polynomials. If set to
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% NAN, the polynomials will be eliminated by forcing the
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% coefficients to zero
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%
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% See also UNCERTAIN
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[varargout{1:nargout}] = robustify(varargin{:});
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