In the actual microbial fermentation process,excessive or insufficient substrate can produce inhibitory effects on cells growth.The artificial substrate feeding rules by past experiences have great blindness to keep s...In the actual microbial fermentation process,excessive or insufficient substrate can produce inhibitory effects on cells growth.The artificial substrate feeding rules by past experiences have great blindness to keep substrate concentration in a given appropriate range.This paper considers that alkali feed depends on pH value of the solution and glycerol feed depends on glycerol concentration of the solution in the uncoupled microbial fed-hatch fermentation process,and establishes a state-dependent switched system in which the flow rates of glycerol and alkali,the number of mode switches,the mode sequence and the switching times are prior unknown.To maximize the yield of target product 1,3-Propanediol(1,3-PD),we formulate a switching optimal control problem with the flow rates of glycerol and alkali,the number of mode switches,the mode sequence and the switching times as decision variables,which is a mixed-integer dynamic programming problem.For solving the mixed-integer dynamic programming problem,the control parametrization technique,the time scaling transformation and the embedded system technology are used to obtain an approximate parameter optimization problem.By using a parallel optimization algorithm,we obtain the optimal control strategies.Under the obtained optimal control strategies,the 1,3-PD yield at the terminal time is increased significantly compared with the previous results.展开更多
In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimizatio...In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.展开更多
基金This work is supported by the National Science Foundation of China(Grant Nos.11771008,11171050 and 11371164)the National Science Foundation for the Youth of China(Grant Nos.11201267,11301051,11301081 and 11401073)+3 种基金the Provincial Natural Science Foundation of Fujian(Grant No.2014J05001)the Fundamental Research Funds for Central Universities in China(Grant DUT15LK25)the China Scholorship Council(CSC,No.201506060121)Natural Science Foundation of Shandong Province,China(Grant No.ZR2017MA005).
文摘In the actual microbial fermentation process,excessive or insufficient substrate can produce inhibitory effects on cells growth.The artificial substrate feeding rules by past experiences have great blindness to keep substrate concentration in a given appropriate range.This paper considers that alkali feed depends on pH value of the solution and glycerol feed depends on glycerol concentration of the solution in the uncoupled microbial fed-hatch fermentation process,and establishes a state-dependent switched system in which the flow rates of glycerol and alkali,the number of mode switches,the mode sequence and the switching times are prior unknown.To maximize the yield of target product 1,3-Propanediol(1,3-PD),we formulate a switching optimal control problem with the flow rates of glycerol and alkali,the number of mode switches,the mode sequence and the switching times as decision variables,which is a mixed-integer dynamic programming problem.For solving the mixed-integer dynamic programming problem,the control parametrization technique,the time scaling transformation and the embedded system technology are used to obtain an approximate parameter optimization problem.By using a parallel optimization algorithm,we obtain the optimal control strategies.Under the obtained optimal control strategies,the 1,3-PD yield at the terminal time is increased significantly compared with the previous results.
基金Supported by the National Natural Science Foundation of China,No.29476248 and Trans-Century Training Program Foundation for the Talents by the State Education Commission.
文摘In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.
