mirror of
https://github.com/KevinMidboe/linguist.git
synced 2025-10-29 17:50:22 +00:00
9bb230d7c8
All of these code samples currently are mis-identified in my repositories. I'm donating them to the cause.
75 lines
2.2 KiB
Matlab
75 lines
2.2 KiB
Matlab
function [dx, y] = adapting_structural_model(t, x, u, varargin)
|
|
%
|
|
% Returns the time derivatives of the states and the output of the
|
|
% structural control model with an adapting controller.
|
|
%
|
|
% Parameters
|
|
% ----------
|
|
% t : double
|
|
% The current time.
|
|
% x : double, size(8, 1)
|
|
% The current state.
|
|
% u : double, size(1, 1)
|
|
% The current input.
|
|
% varargin : cell array
|
|
% m1, m2, m3, m4, b1, b2, b3, b4 : double
|
|
% The slope of the four gains and the offset of the four gains.
|
|
% aux : cell array containing a single structure
|
|
% The structure contains:
|
|
% pars : double, size(1,9)
|
|
% The controller parameters.
|
|
% timeDelay : logical
|
|
% If true a 1st order Pade approximation of the human's time delay
|
|
% is included.
|
|
% plantFirst : integer
|
|
% The number of the first plant.
|
|
% plantSecond : integer
|
|
% The number of the second plant.
|
|
% m : double, size(2, 1)
|
|
% The slope of the transfer function adaption function.
|
|
% b : double, size(2, 1)
|
|
% The offset of the transfer function adaption function.
|
|
%
|
|
% Returns
|
|
% -------
|
|
% dx : double, size(8, 1)
|
|
% The derivatives of the states.
|
|
% y : double, size(1, 1)
|
|
% The output, theta.
|
|
|
|
% MATLAB SUCKS! This is unbelievable. On the first iteration varargin is 1x2
|
|
% and after that it is 1x9.
|
|
%size(varargin, 2)
|
|
|
|
% Unpack varargin.
|
|
aux = varargin{end}{1};
|
|
m = zeros(4, 1);
|
|
b = zeros(4, 1);
|
|
for i=1:4
|
|
if size(varargin, 2) == 2
|
|
m(i) = varargin{1}(i);
|
|
b(i) = varargin{1}(i + 4);
|
|
elseif size(varargin, 2) == 9
|
|
m(i) = varargin{i};
|
|
b(i) = varargin{i + 4};
|
|
else
|
|
display('Matlab is stupid.')
|
|
end
|
|
end
|
|
|
|
% First compute the gains at this time.
|
|
aux.pars(1:4) = m .* t + b;
|
|
% Compute the controller.
|
|
Yp = human(aux.pars, aux.timeDelay);
|
|
% Compute the plant and this time.
|
|
c1 = aux.m(1) * t + aux.b(1) + 1e-10;
|
|
c2 = aux.m(2) * t + aux.b(2) + 1e-10;
|
|
Yc = parallel(c1 * plant(aux.plantFirst), c2 * plant(aux.plantSecond));
|
|
% Compute the closed loop system.
|
|
Ys = feedback(Yp * Yc, 1);
|
|
% Convert to state space.
|
|
[A, B, C, D] = tf2ss(Ys.num{1}, Ys.den{1});
|
|
% Compute the derivatives of the states and the outputs.
|
|
dx = A * x + B * u;
|
|
y = C * x + D * u;
|