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%
% MIT No Attribution
%
% Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl, KU Leuven.
%
% Permission is hereby granted, free of charge, to any person obtaining a copy of this
% software and associated documentation files (the "Software"), to deal in the Software
% without restriction, including without limitation the rights to use, copy, modify,
% merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
% permit persons to whom the Software is furnished to do so.
%
% THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
% INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
% PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
% HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
% OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
% SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
%
%
% An implementation of direct collocation
% Joel Andersson, 2016
import casadi.*
% Degree of interpolating polynomial
d = 3;
% Get collocation points
tau_root = [0 collocation_points(d, 'legendre')];
% Coefficients of the collocation equation
C = zeros(d+1,d+1);
% Coefficients of the continuity equation
D = zeros(d+1, 1);
% Coefficients of the quadrature function
B = zeros(d+1, 1);
% Construct polynomial basis
for j=1:d+1
% Construct Lagrange polynomials to get the polynomial basis at the collocation point
coeff = 1;
for r=1:d+1
if r ~= j
coeff = conv(coeff, [1, -tau_root(r)]);
coeff = coeff / (tau_root(j)-tau_root(r));
end
end
% Evaluate the polynomial at the final time to get the coefficients of the continuity equation
D(j) = polyval(coeff, 1.0);
% Evaluate the time derivative of the polynomial at all collocation points to get the coefficients of the continuity equation
pder = polyder(coeff);
for r=1:d+1
C(j,r) = polyval(pder, tau_root(r));
end
% Evaluate the integral of the polynomial to get the coefficients of the quadrature function
pint = polyint(coeff);
B(j) = polyval(pint, 1.0);
end
% Time horizon
T = 10;
% Declare model variables
x1 = SX.sym('x1');
x2 = SX.sym('x2');
x = [x1; x2];
u = SX.sym('u');
% Model equations
xdot = [(1-x2^2)*x1 - x2 + u; x1];
% Objective term
L = x1^2 + x2^2 + u^2;
% Continuous time dynamics
f = Function('f', {x, u}, {xdot, L});
% Control discretization
N = 20; % number of control intervals
h = T/N;
% Start with an empty NLP
w={};
w0 = [];
lbw = [];
ubw = [];
J = 0;
g={};
lbg = [];
ubg = [];
% "Lift" initial conditions
Xk = MX.sym('X0', 2);
w = {w{:}, Xk};
lbw = [lbw; 0; 1];
ubw = [ubw; 0; 1];
w0 = [w0; 0; 1];
% Formulate the NLP
for k=0:N-1
% New NLP variable for the control
Uk = MX.sym(['U_' num2str(k)]);
w = {w{:}, Uk};
lbw = [lbw; -1];
ubw = [ubw; 1];
w0 = [w0; 0];
% State at collocation points
Xkj = {};
for j=1:d
Xkj{j} = MX.sym(['X_' num2str(k) '_' num2str(j)], 2);
w = {w{:}, Xkj{j}};
lbw = [lbw; -0.25; -inf];
ubw = [ubw; inf; inf];
w0 = [w0; 0; 0];
end
% Loop over collocation points
Xk_end = D(1)*Xk;
for j=1:d
% Expression for the state derivative at the collocation point
xp = C(1,j+1)*Xk;
for r=1:d
xp = xp + C(r+1,j+1)*Xkj{r};
end
% Append collocation equations
[fj, qj] = f(Xkj{j},Uk);
g = {g{:}, h*fj - xp};
lbg = [lbg; 0; 0];
ubg = [ubg; 0; 0];
% Add contribution to the end state
Xk_end = Xk_end + D(j+1)*Xkj{j};
% Add contribution to quadrature function
J = J + B(j+1)*qj*h;
end
% New NLP variable for state at end of interval
Xk = MX.sym(['X_' num2str(k+1)], 2);
w = {w{:}, Xk};
lbw = [lbw; -0.25; -inf];
ubw = [ubw; inf; inf];
w0 = [w0; 0; 0];
% Add equality constraint
g = {g{:}, Xk_end-Xk};
lbg = [lbg; 0; 0];
ubg = [ubg; 0; 0];
end
% Create an NLP solver
prob = struct('f', J, 'x', vertcat(w{:}), 'g', vertcat(g{:}));
solver = nlpsol('solver', 'ipopt', prob);
% Solve the NLP
sol = solver('x0', w0, 'lbx', lbw, 'ubx', ubw,...
'lbg', lbg, 'ubg', ubg);
w_opt = full(sol.x);
% Plot the solution
x1_opt = w_opt(1:3+2*d:end);
x2_opt = w_opt(2:3+2*d:end);
u_opt = w_opt(3:3+2*d:end);
tgrid = linspace(0, T, N+1);
clf;
hold on
plot(tgrid, x1_opt, '--')
plot(tgrid, x2_opt, '-')
stairs(tgrid, [u_opt; nan], '-.')
xlabel('t')
legend('x1','x2','u')
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