Robust Control of Propane Pre-Cooled Mixed Refrigerant Process for Natural Gas Liquefaction
This paper appears in:
Control Automation and Systems (ICCAS), 2010 International Conference on
Date of Conference: 27-30 Oct. 2010
Author(s): Khan, M.S.
Sch. of Chem. Eng. & Technol., Yeungnam Univ., Gyeongsan, South Korea
Mun Kyu Yoon ; Husnil, Y.A. ; Moonyong Lee
On Page(s): 702 - 706
Product Type: Conference Publications
Natural Gas are often found at remote locations to bring it to the world market liquefaction is required. In... more Natural Gas are often found at remote locations to bring it to the world market liquefaction is required. In liquefaction natural gas is cooled to around -160°C, hence required considerable amount of energy. To maximize the profit from the existing design it is necessary that the process should operate efficiently, reliably and safely. Hence a good and Robust control is required. Due to tight control strategy the stability is an issue in the main cryogenic heat exchanger(MCHE) and in the Refrigerant flash drum. In this study the C3MR process was considered and the dynamic model was made in Hysys simulator and used to implement the proposed control algorithm. By judiciously choosing control variables we have proposed more robust control strategy and its performance was observed under simulation environment which provide satisfactory robustness for stability and performance.
Automated Optimization of Process Plant Using Particle Swarm Optimization
This paper appears in:
Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on
Date of Conference: 23-26 May 2011
Author(s): Khan, M.S.
Sch. of Chem. Eng., Yeungnam Univ., Gyeongsan, South Korea
Husnil, Y.A. ; Yong Soo Kwon ; Moonyong Lee
On Page(s): 615 - 620
Product Type: Conference Publications
Nowadays general-purpose process plant simulators are used widely in industry and in academia, reason being process... more Nowadays general-purpose process plant simulators are used widely in industry and in academia, reason being process model can be developed more rigorously with fewer endeavors and the graphical user interface makes the realization of model less time consuming. During the development phase of a process model we often have a lot of variables that has to vary to get the best solution among several candidates. The automation potential of the simulator can be exploited to look for the best solution by varying these variables under some optimization scheme. In this study the Particle Swarm Optimization was used to optimize the process plant under the automation of process simulator Hysys. In the case study Natural Gas liquefaction plant was used to optimize and results show that the method can save energy and improves the process efficiency.
A novel approach to policy design using process design principles
Araz Taeihagh, René Bañares-Alcántara and Zun Wang, ‘A novel approach to policy design using process design principles’, Computer Aided Chemical Engineering, Volume 27, 2009, Pages 2049-2054. http://dx.doi.org/10.1016/S1570-7946(09)70732-1
DownloadHadjiandreou M.M., Conejeros R., Vassiliadis V.S. (2007). Towards a long-term model construction for the dynamic simulation of HIV infection, Mathematical Biosciences and Engineering 4, 489-504.
This study involves the mathematical modelling of long-term HIV dynamics. The proposed model is able to predict the... more This study involves the mathematical modelling of long-term HIV dynamics. The proposed model is able to predict the entire trajectory of the disease: initial viremia in the early weeks of the infection, latency, and progression to AIDS; a range spanning approximately ten years. The model outcomes were compared to clinical data and significant agreement was achieved. The formulated model considers all important population compartments including macrophages, latently-infected CD4+ T-cells, and cytotoxic T-lymphocytes (CTLs), an attempt which in many respects is novel in the area of HIV modelling. The ranges of the model parameters and initial conditions were obtained from literature, and their values were determined in this work directly by fitting published clinical data. Furthermore, the simulation results emphasize the importance of macrophages in HIV infection and progression to AIDS and show a clear correlation between the level of CTLs and HIV progression. The ability of the model to correlate analytical data gives credibility to its predictions, a fact that will be exploited in future research in modelling immunological and pharmacological avenues of treatment.
Hadjiandreou M.M., Conejeros R., Vassiliadis V.S., Wilson D.I. (2008). Long-term HIV dynamics: Mathematical modeling and optimal control, Proceedings of The 2008 International Conference on Bioinformatics and Computational Biology, Las Vegas, Nevada, USA, 2, 444-450.
This study involves the mathematical modeling of long-term HIV dynamics and the investigation of optimal treatment... more
This study involves the mathematical modeling of long-term HIV dynamics and the investigation of optimal treatment strategies. The model duplicates literaturereported clinical data with good agreement and is able to predict the entire trajectory of the disease. The model is extended to account for therapy and the emergence of drugresistant virus and used to investigate how continuous therapy and Structured Treatment Interruptions (STIs) can be implemented in an optimal manner to extend the lifeexpectancy of an HIV-infected patient to desirable times, while at the same time minimizing drug-related side-effects. Whereas the former fails when treating patients that have developed strong drug resistance, STIs prove to be very promising. This is because the optimal schedule of ON and OFF treatment allows for the interplay between the drugsensitive and drug-resistant virus and prevents them from growing in an uncontrolled manner. As a result, uninfected CD4+ T-cells are maintained at relatively high values at all times.
Keywords: Drug efficacy, resistance, therapy, STIs.
Hadjiandreou M.M., Conejeros R., Wilson D.I. (2009). HIV treatment planning on a case-by-case basis. International Journal of Biological and Life Sciences. 6, 148-157.
This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The... more
This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.
Keywords - AIDS; chemotherapy; mathematical modeling; optimal control; progression.
Hadjiandreou M.M., Conejeros R., Wilson D.I. (2009). Long-term HIV dynamics subject to continuous therapy and structured treatment interruptions, Chemical Engineering Science 64, 1600-1617.
This study involves the mathematical modelling of long-term HIV dynamics and the investigation of optimal treatment... more
This study involves the mathematical modelling of long-term HIV dynamics and the investigation of optimal treatment strategies. In our previous work, we produced a model which replicates literature-reported clinical data from untreated patients with good agreement and is able to predict the entire trajectory of the disease. Here, we extend the model to account for therapy and the emergence of virus resistant to antiretroviral drugs. We compare the new model with clinical data and use it to investigate the effect of continuous and interrupted (structured treatment interruptions, STI) therapy. For the former, there exist optimal combinations of reverse transcriptase inhibitor (RTI) and protease inhibitor (PI) drug efficacies for which both the wild-type (drug-sensitive) virus is depleted and the time at which mutated (drug-resistant) virus becomes dominant is extended. The simulation results also suggest that ‘PI-based’ drug regimes work better than ‘RTI-based’ ones. For STIs, there exists an optimised schedule of ON and OFF treatment by which the interplay between drug-sensitive and drug-resistant virus does not allow either of them to grow in an uncontrolled manner and deplete CD4+ T-cells (the main target of HIV: they ‘orchestrate’ the immune response). Furthermore, the schedule minimises the impact of side-effects that may arise during therapy. The results show that an optimised schedule, facilitating the interplay between the two virus strains, is the key to the successful implementation of STIs, which have so far been unsuccessful in extending survival-time considerably. Whereas continuous therapy fails when treating patients that have developed strong drug resistance, STIs prove to be very promising. The simulation and optimisation results indicate that although complete eradication of the virus may not be possible, controlling it over a considerable length of time is feasible.
Keywords: Mathematical modelling; Optimal control; Chemotherapy; Drug resistance
Hadjiandreou M.M., Conejeros R., Wilson D.I. (2009). Planning of patient-specific drug-specific optimal HIV treatment strategies. Chemical Engineering Science 64, 4024-4039.
In this study, we present a mathematical modelling and optimal control approach to formulate patient-specific... more
In this study, we present a mathematical modelling and optimal control approach to formulate patient-specific drug-specific treatment strategies for HIV-infected patients. Central to this is the fact that no two individuals respond to infection and treatment in quite the same way, and that different drugs are associated with varied efficacies in the body as well as with different side-effects. We hereby present a methodology which allows optimal planning on a case-by-case basis, unlike previous work in the field which formulated treatment protocols for general use by considering drug efficacies only. Investigation of optimal strategies by using models which consider the pharmacokinetic behaviour of drugs as well as their side-effects by using a well-documented chart may be considered a novel contribution and allows for the optimum administration of all drugs depending on their degree of toxicity as well as their effectiveness in the body. The formulated model is able to replicate clinical data from different progressors to AIDS by estimation of immune system parameters only. The latter have been suggested to be key in determining the degree of progression and the ability of the model to reproduce this phenomenon further validates the formulation. Optimal treatment strategies are produced for different patients and we can conclude that a general treatment protocol cannot be proposed and therapy has to be designed on an individual basis.
Keywords: Mathematical modelling; Optimal control; Chemotherapy; Side-effect; Drug resistance; Progression