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Denbigh Reaction: Difference between revisions

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<span id="Luus">[2]</span> Rein Luus, Iterative Dynamic Programming. CHAPMAN & HALL/CRC Monographs and Surveys in Pure and Applied Mathematics, New York, 2000.<br>
<span id="Luus">[2]</span> Rein Luus, Iterative Dynamic Programming. CHAPMAN & HALL/CRC Monographs and Surveys in Pure and Applied Mathematics, New York, 2000.<br>
<span id="Denbigh">[3]</span> Kenneth Denbigh, Chemical Reactor Theory an Introduction, Cambridge University Press, London, 1965.<br>
<span id="Denbigh">[3]</span> Kenneth Denbigh, Chemical Reactor Theory an Introduction, Cambridge University Press, London, 1965.<br>
<span id="Tomlab">[3]</span> Tomlab optimization: https://tomopt.com/docs/propt/tomlab_propt030.php<br>
<span id="Tomlab">[4]</span> Tomlab optimization: https://tomopt.com/docs/propt/tomlab_propt030.php<br>


[[Category:MIOCP]]
[[Category:MIOCP]]
[[Category:Bang bang]]
[[Category:Bang bang]]

Revision as of 10:59, 21 August 2025

Denbigh Reaction
State dimension: 1
Differential states: 3
Discrete control functions: 1


The Mountain Car problem s based on the system of chemical reactions initially considered by Denbigh (1958), which was also studied by Aris (1960) and more recently by Luus (1994):

A+BXXQXYA+XP

where X is an intermediate, Y is the desired product, and P and Q are waste products. The optimal control problem is to find T(t) (the temperature of the reactor as a function of time) so that the yield of Y is maximized at the end of the given batch time tf.

Its dynamics are given by a three-dimensional ODE model. The optimal integer control functions exhibits a bang bang structure.

Mathematical formulation

maxux3(tf)subject tox1˙(t)=k1(t)x1(t)k2(t)x1(t),x2˙(t)=k1(t)x1(t)k3(t)+k4(t)x2(t),x3˙(t)=k3(t)x2(t),ki(t)=ki*exp(EiT(t)), i=1,,4,T(t)[273,415] t[0,tf]x(0)=(1,0,0)T

Parameters

Parameters
Symbol Value
E1 103
E2 107
E3 10
E4 103
k1* 3103
k2* 6103
k3* 3103
k4* 0
tf 103


Reference Solutions

Here is one local solution to the above control problem.

Miscellaneous and Further Reading

This formulation and a detailed description can be found in [1].

References

[1] Rutherford Aris. The Optimal Design of Chemical Reactors A Study in Dynamic Programming. Academic Press, London, 1961.
[2] Rein Luus, Iterative Dynamic Programming. CHAPMAN & HALL/CRC Monographs and Surveys in Pure and Applied Mathematics, New York, 2000.
[3] Kenneth Denbigh, Chemical Reactor Theory an Introduction, Cambridge University Press, London, 1965.
[4] Tomlab optimization: https://tomopt.com/docs/propt/tomlab_propt030.php