xxsimLinearizeModel

 xxsimLinearizeModel - SISO linearization.

 Syntax: 
   retval = xxsimLinearizeModel(u, y, symbolic = true, atCurrentTime = true, closedLoop = false, absError = 1.0e-5, relError = 1.0e-5, useAbsWhenNeeded = true)

 Inputs:
   u = (string) input name.
   y = (string) output name.
   symbolic = (boolean, optional) true indicates that a symbolic linerarization should be done, false performs a numerical linearization. Default = true.
   atCurrentTime = (boolean, optional) true indicates that the linerarization should be done at the current time, false at simulation start. Default = true.
   closedLoop = (boolean, optional) indicates openloop (false) or closed loop response (true). Default = true.
   absError = (float, optional) the absolute change in states. Default = 1.0e-5.
   relError = (float, optional) the relative change in states. Default = 1.0e-5.
 
 Outputs: 
   retval = [A,B,C,D] matrices.

 Examples:
   xxsimLinearizeModel('Submodel.u', 'Submodel.y');

 Author: Controllab Products B.V.
 email: info@controllab.nl
 Website: http://www.controllab.nl
 October 2014

0001 function [A, B, C, D] = xxsimLinearizeModel(u, y, varargin)
0002 % xxsimLinearizeModel - SISO linearization.
0003 %
0004 % Syntax:
0005 %   retval = xxsimLinearizeModel(u, y, symbolic = true, atCurrentTime = true, closedLoop = false, absError = 1.0e-5, relError = 1.0e-5, useAbsWhenNeeded = true)
0006 %
0007 % Inputs:
0008 %   u = (string) input name.
0009 %   y = (string) output name.
0010 %   symbolic = (boolean, optional) true indicates that a symbolic linerarization should be done, false performs a numerical linearization. Default = true.
0011 %   atCurrentTime = (boolean, optional) true indicates that the linerarization should be done at the current time, false at simulation start. Default = true.
0012 %   closedLoop = (boolean, optional) indicates openloop (false) or closed loop response (true). Default = true.
0013 %   absError = (float, optional) the absolute change in states. Default = 1.0e-5.
0014 %   relError = (float, optional) the relative change in states. Default = 1.0e-5.
0015 %
0016 % Outputs:
0017 %   retval = [A,B,C,D] matrices.
0018 %
0019 % Examples:
0020 %   xxsimLinearizeModel('Submodel.u', 'Submodel.y');
0021 %
0022 % Author: Controllab Products B.V.
0023 % email: info@controllab.nl
0024 % Website: http://www.controllab.nl
0025 % October 2014
0026 
0027 %------------- BEGIN CODE --------------
0028     retval = false;
0029 
0030     % set default arguments
0031     symbolic = true;
0032     atCurrentTime = true;
0033     closedLoop = false;
0034     absError = 1.0e-5;
0035     relError = 1.0e-5;
0036     useAbsWhenNeeded = true;
0037     
0038     % override them with the optional arguments:
0039     if nargin > 2, symbolic = varargin{1}; end
0040     if nargin > 3, atCurrentTime = varargin{2}; end
0041     if nargin > 4, closedLoop = varargin{3}; end
0042     if nargin > 5, absError = varargin{4}; end
0043     if nargin > 6, relError = varargin{5}; end
0044     if nargin > 7, useAbsWhenNeeded = varargin{6}; end
0045 
0046     % embed string inputs in a cell when needed
0047     if iscell(u)
0048         use_u = u;
0049       else
0050             use_u = {u};
0051     end
0052     if iscell(y)
0053         use_y = y;
0054     else
0055         use_y = {y};
0056     end
0057 
0058     % start with empty matrices
0059     A = []; B = []; C = []; D = [];
0060 
0061     % get the amount of inputs and outputs
0062     k = length (use_u);
0063     p = length (use_y);
0064     
0065     % temporary fix until the MIMO support is well tested
0066     for k_ = 1:k
0067       use_u_ = use_u{k_};
0068       for p_ = 1:p
0069         use_y_ = use_y{p_};
0070         
0071         % call 20-sim itself
0072         s =  struct('u', {{ {use_u_}, 'array' }}, 'y', {{ {use_y_}, 'array' }}, 'symbolic', symbolic, 'atCurrentTime', atCurrentTime, 'closedLoop', closedLoop, 'absError', absError, 'relError', relError, 'useAbsWhenNeeded', useAbsWhenNeeded);
0073         retval = xrlinvoke('xxsim.model.linearizeModel', s);
0074         
0075         % get the amount of states
0076         n = sqrt(length(retval.A));
0077         
0078         % fill the matrices
0079         A        = transpose (reshape(retval.A, n, n));
0080         B(:,k_)  = retval.B;
0081         C(p_,:)  = retval.C;
0082         D(p_,k_) = retval.D;
0083       end
0084     end    
0085 end
0086 %------------- END OF CODE --------------