Specify fixed variable variations for an augmented d-optimal design

I have a performed an experiment according to the design Matrix 'startdes'. Now I want to add one run to the design (nruns = 1). Furthermore I have speficied my new 'model'. I use the following function.

[settings, X] = daugment(startdes,nruns,model,varargin)

Now here comes the problem, I want to use the extra function 'bounds' to specify which values can be chosen for the design. This is possible by specifying a cell array containing NFACTORS elements, each element specifying the vector of allowable values for the corresponding factor (see fat text).

% 'bounds' Lower and upper bounds for each factor, specified % as a 2-by-NFACTORS matrix, where NFACTORS is the % number of factors. Alternatively, this value can % be a cell array containing NFACTORS elements, each % element specifying the vector of allowable values for % the corresponding factor.

When I perform this, the output (X) still contains a value not specified in the bounds cell arrays. Since the settings of my variables are fixed this is a problem.

Does anyone know how to make a D-Optimal augmented design for fixed set of variable settings.

Thanks in advance, greetings,

Jelle