A hybrid method for the optimal control of chemical processes

Carrasco, Eugenio F.; Banga, Julio R.

doi:10.1049/cp:19980352

Cited by 19 publications

(12 citation statements)

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“…Regarding the global search phase of the hybrid, in our group, and during the last decade, we have compared a number of different stochastic and deterministic global optimisation methods, making particular emphasis on the optimisation of non-linear dynamic systems (Banga and Seider, 1996;Banga et al, 1997Banga et al, , 2003Balsa-Canto et al, 1998;Carrasco and Banga, 1998;Moles et al, 2003a,b). The overall conclusions from these studies indicate that modern Evolution Strategies (Hansen and Ostermeier, 2001;Runarsson and Yao, 2000) have several key advantages over GAs and SA, namely better efficiency/robustness ratio, good scaling properties (i.e.…”

Section: Global Optimisation: Hybrid Methodsmentioning

confidence: 99%

A hybrid approach for efficient and robust parameter estimation in biochemical pathways

Rodríguez-Fernández¹,

Mendes

Banga³

2006

Biosystems

255

216

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Section: Global Optimisation: Hybrid Methodsmentioning

confidence: 99%

A hybrid approach for efficient and robust parameter estimation in biochemical pathways

Rodríguez-Fernández¹,

Mendes

Banga³

2006

Biosystems

255

216

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“…Carrasco et al combined the stochastic and deterministic technique to solve this problem . Mekarapiruk and Luus solved this problem by the method of iterative dynamic programming and got a result of 0.677 27 .…”

Section: Case Studiesmentioning

confidence: 99%

An effective pseudospectral optimization approach with sparse variable time nodes for maximum production of chemical engineering problems

Xiao

Liu

2017

Can J Chem Eng

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An effective pseudospectral method is proposed for dynamic optimization problems, the aim of which is to maximize production of these problems in chemical engineering. Several variable time nodes are considered to be optimization variables in the whole time horizon to obtain a precise localization of the switching points of the optimal control profiles. To ensure accuracy, the intervals between the variable time nodes are further divided into multiple subintervals uniformly. Then the state and the control vector are all parameterized. To improve the efficiency, the sensitivities of the states with respect to the controls and the variable time nodes are derived from the solution of the discretized dynamic system. Three chemical dynamic optimization problems are tested as an illustration. The detailed comparisons between the proposed method and the methods reported in the literature are also carried out. The research results reveal the effectiveness of the proposed approach.

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“…This problem considers the optimal control of a fedbatch reactor for induced foreign protein production by recombinant bacteria, as presented by Lee and Ramirez [12] and considered afterwards by Tholudur and Ramirez [20] and Carrasco and Banga [5]. They used the optimal control theory and showed the existence of singular control arcs for this system.…”

Section: Model Of Fed-batch Bioreactormentioning

confidence: 99%

Optimal feeding profile for a fuzzy logic controller in a bioreactors using genetic algorithm

Mokeddem

Khellaf

2011

Nonlinear Dyn

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The ultimate objective of any control strategy is to maximize productivity, and improve the quantity of products and reduce costs. The performance of a bioprocess operating in fed batch production of protein can be obtained in two steps. First, we determine the optimal trajectories (profiles) for the variables of interests and then a genetic algorithm based on a fuzzy logic controller is applied to regulate these variables around these profiles.An optimal feeding profile of a fed batch process based on an evolutionary algorithm is designed. This algorithm is well suited to derive multi-objective optimization, since it involves a set of non-dominated solutions distributed along the Pareto front. Several evolutionary multi-objective optimization algorithms have been developed in which the Non-dominated Sorting Genetic Algorithm NSGA-II is recognized to be very effective to overcome a variety of problems; an optimal control problem, usually solved by several methods considering single-objective dynamic optimization, is worked out.

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A hybrid method for the optimal control of chemical processes

Cited by 19 publications

References 0 publications

A hybrid approach for efficient and robust parameter estimation in biochemical pathways

A hybrid approach for efficient and robust parameter estimation in biochemical pathways

An effective pseudospectral optimization approach with sparse variable time nodes for maximum production of chemical engineering problems

Optimal feeding profile for a fuzzy logic controller in a bioreactors using genetic algorithm

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