Optimal control methodologies for the optimisation of maintenance scheduling and production in processes using decaying catalysts

In this thesis, optimal control methodologies are developed for solving problems involving the optimisation of maintenance scheduling and production in processes using decaying catalysts. Previously, such problems were solved using a category of methods which involve making decisions of discrete as well as continuous nature, called mixed-integer optimisation techniques. However, these techniques are combinatorial in nature and can solve differential equations only by approximations as collections of steady state equality constraints, and such features can cause these techniques difficulties in obtaining optimal and accurate solutions for these problems. The goal behind developing optimal control methodologies is to effectively solve these problems while overcoming the drawbacks that mixed-integer optimisation techniques face or would face in solving these problems. First, an optimal control methodology is developed to optimise maintenance scheduling and production in a process containing a reactor using decaying catalysts. This methodology involves using a multistage mixed-integer optimal control problem (MSMIOCP) formulation and obtaining solutions as a standard nonlinear optimisation problem, without using mixed-integer optimisation techniques. Two different solution implementations are required, each which has its own relative advantages. The methodology using the second procedure is particularly successful in effectively obtaining solutions within the stipulated tolerances. Further, the methodology possesses features of robustness because it enables a relatively small problem size, reliability because it solves differential equations using state-of-the-art integrators, and efficiency because it is not combinatorial in nature. These features indicate the methodology’s success in overcoming the drawbacks of using mixed-integer optimisation techniques to solve this problem. Next, the abovementioned methodology is extended to form an optimal control methodology to optimise maintenance scheduling and production in a process containing parallel lines of reactors using decaying catalysts. This methodology, when applied to a case study of such a process, is also able to effectively obtain solutions within the stipulated tolerances. Further, the solutions obtained, once again, possess features of robustness, reliability and efficiency, which indicate that the methodology can overcome the drawbacks that mixed-integer optimisation techniques would face, if used to solve such problems. And lastly, an optimal control methodology is developed for considering uncertainties in kinetic parameters in the optimisation of maintenance scheduling and production in a process containing a reactor using decaying catalysts. The methodology involves using a multiple scenario approach to consider parametric uncertainties and formulating a stochastic MSMIOCP, which is solved as a standard nonlinear optimisation problem as per the previously developed procedure. The results obtained provide insights into the effects of parametric uncertainties and the number of scenarios generated on the optimal operations, and indicate that the methodology is capable of solving this problem. Further, the robust, reliable and efficient nature of the results obtained suggest that the methodology can overcome the disadvantages that mixed-integer methods would introduce in the conventional methodologies, if such methodologies are used to solve such problems.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2020

Author dc:creator

• Adloor, Saidarshan

Advisor dc:contributor.advisor

• Lapkin, Alexei

• Optimal control problem
• Bang-bang control
• Mixed-integer optimisation
• Catalyst replacement
• Maintenance scheduling
• Production planning

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/4e8244aa-986b-4b5f-9964-47a692723239/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0001-7621-0889

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/325027