PROPT Catalyst Mixing

From TomWiki
Jump to navigationJump to search

Notice.png

This page is part of the PROPT Manual. See PROPT Manual.

Second-order sensitivities of general dynamic systems with application to optimal control problems. 1999, Vassilios S. Vassiliadis, Eva Balsa Canto, Julio R. Banga

Case Study 6.2: Catalyst mixing

Problem formulation

This problem considers a plug-flow reactor, packed with two catalysts, involving the reactions

S1 <-> S2 -> S3

The optimal mixing policy of the two catalysts has to be determined in order to maximize the production of species S3. This dynamic optimization problem was originally proposed by Gunn and Thomas (1965), and subsequently considered by Logsdon (1990) and Vassiliadis (1993). The mathematical formulation is

Maximize:


subject to:


% Copyright (c) 2007-2008 by Tomlab Optimization Inc.

Problem setup

toms t
p = tomPhase('p', t, 0, 1, 30);
setPhase(p);

tomStates x1 x2
tomControls u

% Initial guess
% Note: The guess for t_f must appear in the list before expression involving t.
x0 = {icollocate({
    x1 == 1-0.085*t
    x2 == 0.05*t
    })
    collocate(u==1-t)};

% Box constraints
cbox = {0.9 <= icollocate(x1) <= 1
    0 <= icollocate(x2) <= 0.1
    0 <= collocate(u)   <= 1};

% Boundary constraints
cbnd = {initial({x1 == 1; x2 == 0})
    final({x1 <= 0.95})};

% ODEs and path constraints
ceq = collocate({
    dot(x1) == u.*(10*x2-x1)
    dot(x2) == u.*(x1-10*x2)-(1-u).*x2});

% Objective
objective = -1+final(x1)+final(x2);

Solve the problem

options = struct;
options.name = 'Catalyst Mixing';
solution = ezsolve(objective, {cbox, cbnd, ceq}, x0, options);
t  = subs(collocate(t),solution);
x1 = subs(collocate(x1),solution);
x2 = subs(collocate(x2),solution);
u  = subs(collocate(u),solution);
Problem type appears to be: lpcon
Time for symbolic processing: 0.10689 seconds
Starting numeric solver
===== * * * =================================================================== * * *
TOMLAB - TOMLAB Development license  999007. Valid to 2011-12-31
=====================================================================================
Problem: ---  1: Catalyst Mixing                f_k      -0.048059280695325057
                                       sum(|constr|)      0.000000452031611660
                              f(x_k) + sum(|constr|)     -0.048058828663713395
                                              f(x_0)      0.964999999999998080

Solver: snopt.  EXIT=0.  INFORM=1.
SNOPT 7.2-5 NLP code
Optimality conditions satisfied

FuncEv    1 ConstrEv   66 ConJacEv   66 Iter   43 MinorIter  248
CPU time: 0.062400 sec. Elapsed time: 0.059000 sec. 

Plot result

subplot(2,1,1)
plot(t,x1,'*-',t,x2,'*-');
legend('x1','x2');
title('Catalyst Mixing state variables');

subplot(2,1,2)
plot(t,u,'+-');
legend('u');
title('Catalyst Mixing control');

CatalystMixing 01.png