Dynamic-Calibration/utils/YALMIP-master/extras/@ncvar/abs.m

74 lines
2.6 KiB
Matlab
Executable File

function varargout=abs(varargin)
%ABS (overloaded)
%
% t = abs(x)
%
% The variable t can only be used in convexity preserving
% operations such as t<=0, minimize t etc.
%% ***************************************************
% This file defines a nonlinear operator for YALMIP
%
% It can take three different inputs
% For double inputs, it returns standard double values
% For sdpvar inputs, it genreates a an internal variable
% When first input is 'model' it generates the epigraph
%% ***************************************************
switch class(varargin{1})
case 'double'
error('Overloaded SDPVAR/ABS CALLED WITH DOUBLE. Report error')
case 'sdpvar' % Overloaded operator for SDPVAR objects. Pass on args and save them.
if isreal(varargin{1})
varargout{1} = yalmip('addextendedvariable',mfilename,varargin{1});
else
% For complex args, abs(X) is defined [norm(X(i,j),2)] in MATLAB
y = [];
x = varargin{1};
for i = 1:size(x,1)
temp = [];
for j = 1:size(x,2)
temp = [temp norm(extsubsref(x,i,j))];
end
y = [y;temp];
end
varargout{1} = y;
end
case 'char' % YALMIP send 'graph' when it wants the epigraph or hypograph
switch varargin{1}
case 'graph'
% Description using epigraphs
t = varargin{2};
X = varargin{3};
varargout{1} = (-t <= X <= t);
varargout{2} = struct('convexity','convex','monotonicity','none','definiteness','positive');
varargout{3} = X;
case 'milp'
% Exact description using binary variables
t = varargin{2};
X = varargin{3};
F = ([]);
[M,m]=derivebounds(X);
if m>=0
F = F + (t == X);
elseif M<0
F = F + (t == -X);
else
d = binvar(1,1);
F = F + (X <= M*d) + (-2*(M-m)*d <= t+X <= 2*(M-m)*d);
F = F + (X >= m*(1-d)) + (-2*(M-m)*(1-d) <= t-X <= 2*(M-m)*(1-d));
end
varargout{1} = F;
varargout{2} = struct('convexity','milp','monotonicity','milp','definiteness','positive');
varargout{3} = X;
otherwise
error('SDPVAR/ABS called with CHAR argument?');
end
otherwise
error('Strange type on first argument in SDPVAR/ABS');
end