riccati_model_default.m

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function model = riccati_model_default()
%function model = riccati_model_default
% This model is the general model for the riccati type
% models for the linear dynamic system:
%
%   E(mu) d/dt x = A(mu)x + B(mu)u
%              y = C(mu)x
%
% The corresponding ARE then reads as follows:
%   A'PE + E'PA - E'PBB'PE + C'C = 0
%
% This function sets the following fields in the model
%   mu_names
%   mu_ranges
%   set_mu
%   get_mu
%   decomp_mode
% 
% Andreas Schmidt, 2015

model = {};

% Set the default fields for the model:
model.mu_names = {};
model.mu_ranges = {};
model.set_mu = @set_mu_default;
model.get_mu = @get_mu_default;

% The decomp_mode flag is used as usual. All data functions should take
% care of it.
model.decomp_mode = 0;

model.gen_model_data = @riccati_gen_model_data;
model.detailed_simulation = @riccati_detailed_simulation;

model.plot_detailed_data = @riccati_plot_solution;

model.gen_detailed_data = @riccati_gen_detailed_data;
model.gen_reduced_data = @riccati_gen_reduced_data;
model.reduced_data_subset = @riccati_reduced_data_subset;
model.rb_simulation = @riccati_rb_simulation;
model.rb_reconstruction = @riccati_rb_reconstruction;

model.simulate = @riccati_simulate;
model.plot_sim_data = @riccati_plot_sim_data;
model.plot_handle = @(model,model_data,sim) error('Fill plot_handle with contents');
model.plot_controlled = 1;

% Define the matrices:
model.A = @(model,model_data) error('set the A(model,model_data) function');
model.B = @(model,model_data) error('set the B(model,model_data) function');
model.C = @(model,model_data) error('set the C(model,model_data) function');
model.E = @dummy_E;
model.x0 = @dummy_x0;

% Default settings for the basis building process:
model.RB_enable_estimator = 0;
model.RB_generation_mode = 'greedy_uniform_fixed';
model.RB_extension_mode = 'addmultiple';
model.RB_extension_max_per_step = 40;
model.RB_samplepoints = 300;
model.RB_gamma_mode = 'interpol';
model.RB_numintervals = 10;
model.RB_o_tol = 1e-6;
model.RB_i_tol = 1e-4;

%% Auxilliary functions:
% Set dummy values for the E matrix, i.e. it is sparse identity by default
function r = dummy_E(model, model_data)
E = @(model,model_data){speye(model.n)};
r = eval_affine_decomp(E, @(model) 1, model, model_data);

% The default x0 is a normalized constant vector
function r = dummy_x0(model, model_data)
g = [];
if model.decomp_mode < 2
    g = ones(model.n, 1);
    g = g/norm(g);
end
r = eval_affine_decomp(@(m,md) {g}, @(model) 1, model, model_data);