Initial commit

[pftoolbox.git] / models / @danl / danl.m

function obj = pfsys(varargin)\r
% Constructor for the DANL (Discrete Additive Non-Linear) model\r
%\r
% x(t+T) = f(x,t) + gu(x,t)*u(t) + gw(x,t)*w(t)\r
%   y(t) = h(x,t) + hu(x,t)*u(t) + e(t)\r
%\r
% Syntax: (* = optional)\r
%\r
% model = danl(f, gw, gu, h, hu, x0, w, e, p0*, T*, xvars*);\r
% model = danl(ltiobj);\r
%\r
% In arguments:\r
%\r
% 1. f\r
%       Data object containing f.\r
%       If a double (matrix), or a cell array of strings (or inlines) is given, it will be\r
%       used to create an apropriate expression object.\r
%       Note: if a double is given, a xlinear object will be created with 'evalvar' set to 1,\r
%       i.e. the matrix will be multiplied with x when evaluating f(x,t).\r
% 1. ltiobj\r
%       A LTI object (ss, tf or zpk), from the control toolbox. \r
%       Necessary data will be extracted, and normally distributed noise with variance\r
%       1 will be used.\r
% 2. gw\r
%       Data object containing gw\r
%       If a double (matrix), or a cell array of strings (or inlines) is given, it will be\r
%       used to create an apropriate expression object.\r
%       Note: if a double is given, a xlinear object will be created with 'evalvar' set to 0,\r
%       i.e. gw(x,t) is constant and does NOT depend on x.\r
% 3. gu\r
%       Data object containing gu\r
%       If a double (matrix), or a cell array of strings (or inlines) is given, it will be\r
%       used to create an apropriate data object.\r
%       Note: if a double is given, a xlinear object will be created with 'evalvar' set to 0,\r
%       ie gu(x,t) is constant and does NOT depend on x.\r
% 4. h\r
%       Data object containing h\r
%       If a double (matrix), or a cell array of strings (or inlines) is given, it will be\r
%       used to create an apropriate data object.\r
%       Note: if a double is given, a xlinear object will be created with 'evalvar' set to 1,\r
%       ie the matrix will be multiplied with x when evaluating h(x,t).\r
% 5. hu\r
%       Data object containing hu\r
%       If a double (matrix), or a cell array of strings (or inlines) is given, it will be\r
%       used to create an apropriate data object.\r
%       Note: if a double is given, a xlinear object will be created with 'evalvar' set to 0,\r
%       ie hu(x,t) is constant and does NOT depend on x.\r
% 6. x0\r
%       A column vector containing the expectation of the initial state estimate.\r
%       Each row represents a state.\r
% 7. w\r
%       Noise object containing w.\r
%       It can also be a covariance matrix or a vector containing the diagonal of a\r
%       diagonal covariance matrix. This will be used to create a gaussian noise object\r
%       for use as w.\r
% 8. e\r
%       Noise object containing e\r
%       It can also be a covariance matrix or a vector containing the diagonal of a\r
%       diagonal covariance matrix. This will be used to create a gaussian noise object\r
%       for use as e.\r
% 9* p0\r
%       Noise object containing p0, that has to generate tuples of the same size as x0.\r
%       It can also be a covariance matrix or a vector containing the diagonal of a\r
%       diagonal covariance matrix. This will be used to create a gaussian noise object\r
%       for use as p0.\r
% 9* []\r
%       'p0' is set to independent gaussian noise with variance 1.\r
% 10* T\r
%       Sample time.\r
% 10* []\r
%       'T' is set to 1.\r
% 11* xvars\r
%       A cell array containing the names of the states.\r
% 11* []\r
%       'xvars' is set to {'x1', 'x2', 'x3', ...}\r
%\r
% Out arguments:\r
%\r
% 1. model\r
%       The resulting danl model object.\r
\r
% Toolbox for nonlinear filtering.\r
% Copyright (C) 2005  Jakob Rosén <jakob.rosen@gmail.com>\r
%\r
% This program is free software; you can redistribute it and/or\r
% modify it under the terms of the GNU General Public License\r
% as published by the Free Software Foundation; either version 2\r
% of the License, or (at your option) any later version.\r
%\r
% This program is distributed in the hope that it will be useful,\r
% but WITHOUT ANY WARRANTY; without even the implied warranty of\r
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\r
% GNU General Public License for more details.\r
%\r
% You should have received a copy of the GNU General Public License\r
% along with this program; if not, write to the Free Software\r
% Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.\r
\r
if nargin==0\r
        % Empty constructor\r
        % Will create a non-sense object, to satisfy Matlab standards\r
        obj.f=[];\r
        obj.gw=[];\r
        obj.gu=[];\r
        obj.h=[];\r
        obj.hu=[];\r
        obj.x0=[];\r
        obj.w=[];\r
        obj.e=[];\r
        obj.p0=[];\r
        obj.T=1;\r
        obj.xvars={};\r
        obj.description='Discrete Additive Non-Linear model (DANL)';\r
        obj=class(obj,'danl');\r
        return;                         %Exit\r
elseif nargin==1\r
        argin=varargin{1};\r
        if isa(argin,'danl')\r
                % Copy constructor\r
                obj = argin;            %Copy\r
                return;                 %Exit\r
        elseif isa(argin,'ss')||isa(argin,'tf')||isa(argin,'zpk')\r
                % An LTI object was given\r
                obj=lti2danl(argin);    %Convert\r
                return;                 %Exit\r
        end\r
end;\r
\r
error(nargchk(8, 11, nargin));\r
\r
% Fetch gw\r
gwobj=varargin{2};\r
if isempty(gwobj);\r
        % Gw was empty. Set it to 1 (we can't just leave it out)\r
        gwobj=1;\r
end;\r
\r
% Fetch x0\r
x0=varargin{6};\r
if (size(x0,1)==1)&&(size(x0,2)>1);\r
        x0=x0';         % A column vector was supplied. Transpose it!\r
end;\r
\r
% Declare the arguments\r
p0temp=[];\r
T=[];\r
xvars={};\r
\r
% Fetch arguments, if they exist\r
if nargin>=9; p0temp=varargin{9}; end;\r
if nargin>=10; T=varargin{10}; end;\r
if nargin>=11; xvars=varargin{11};  end;\r
\r
% If an empty argument, or no argument at all, was supplied - use its default value!\r
if isempty(p0temp)\r
        p0temp=eye(length(x0)); % p0 default, ind. gaussian noise with variance 1\r
end;\r
\r
if isempty(T)\r
        T=1;                    % T default\r
end;\r
\r
if isempty(xvars)\r
        % Generate a xvar vector\r
        states=length(x0);\r
        xvars=cell(1,states);\r
        for i=1:states\r
                xvars{i}=['x',num2str(i)];\r
        end\r
elseif length(xvars)~=length(x0)\r
        error('The number of elements in ''xvars'' does not match the number of states');\r
end\r
\r
% Initialize the noise (supplied as an argument or generated above)\r
p0=initnoise(p0temp);\r
w=initnoise(varargin{7});\r
e=initnoise(varargin{8});\r
\r
% Initialize data. If xvars={}, default xvars will be calculated\r
f=initdata(varargin{1},xvars,{},{},1);\r
gw=initdata(gwobj,xvars,{},{},0);\r
gu=initdata(varargin{3},xvars,{},{},0);\r
h=initdata(varargin{4},xvars,{},{},1);\r
hu=initdata(varargin{5},xvars,{},{},0);\r
\r
%Initialize object data\r
obj.f=f;\r
obj.gw=gw;\r
obj.gu=gu;\r
obj.h=h;\r
obj.hu=hu;\r
obj.x0=x0;\r
obj.w=w;\r
obj.e=e;\r
obj.p0=p0;\r
obj.T=T;\r
obj.xvars=xvars;\r
obj.description='Discrete Additive Non-Linear model (DANL)';\r
obj=class(obj,'danl');\r