PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY VOLUME 21 JANUARY 2007 ISSN 1307-6884
Optimal Control Problem, Quasi-Assignment Problem and Genetic Algorithm Omid S. Fard and Akbar H. Borzabadi
See paper for failure of GA toolbox algorithm.
Example 1
Find u over t in [0; 1 ] to minimize
| J = | ∫ |
| u2 dt |
subject to:
| = x2 + u |
The initial condition are:
| x(0) = 0 |
| x(1) = 0.5 |
Reference: [17]
toms t
p = tomPhase('p', t, 0, 1, 50);
setPhase(p);
tomStates x
tomControls u
% Initial guess
x0 = {icollocate(x == 0.5*t); collocate(u == 0)};
% Boundary constraints
cbnd = {initial({x == 0}); final({x == 0.5})};
% ODEs and path constraints
ceq = collocate({dot(x) == x.^2+u});
% Objective
objective = integrate(u.^2);
options = struct;
options.name = 'Genetic 1';
solution = ezsolve(objective, {cbnd, ceq}, x0, options);
t = subs(collocate(t),solution);
x = subs(collocate(x),solution);
u = subs(collocate(u),solution);
Problem type appears to be: qpcon
Starting numeric solver
===== * * * =================================================================== * * *
TOMLAB - Tomlab Optimization Inc. Development license 999001. Valid to 2011-02-05
=====================================================================================
Problem: --- 1: Genetic 1 f_k 0.178900993395128240
sum(|constr|) 0.000000000698273828
f(x_k) + sum(|constr|) 0.178900994093402070
f(x_0) 0.000000000000000000
Solver: snopt. EXIT=0. INFORM=1.
SNOPT 7.2-5 NLP code
Optimality conditions satisfied
FuncEv 1 ConstrEv 23 ConJacEv 23 Iter 22 MinorIter 71
CPU time: 0.093750 sec. Elapsed time: 0.094000 sec.
subplot(2,1,1)
plot(t,x,'*-');
legend('x');
title('Genetic 1 state variables');
subplot(2,1,2)
plot(t,u,'+-');
legend('u');
title('Genetic 1 control');