An iterative optimization strategy for fed-batch fermentation process is presented by combining a run-to-run optimization with swarm energy conservation particle swarm optimization (SEC-PSO). SEC-PSO, which is designe...An iterative optimization strategy for fed-batch fermentation process is presented by combining a run-to-run optimization with swarm energy conservation particle swarm optimization (SEC-PSO). SEC-PSO, which is designed with the concept of energy conservation, can solve the problem of premature convergence frequently appeared in standard PSO algorithm by partitioning its population into several sub-swarms according to the energy of the swarm and is used in the optimization strategy for parameter identification and operation condition optimization. The run-to-run optimization exploits the repetitive nature of fed-batch processes in order to deal with the optimal problems of fed-batch fermentation process with inaccurate process model and unsteady process state. The kinetic model parameters, used in the operation condition optimization of the next run, are adjusted by calculating time-series data obtained from real fed-batch process in the run-to-run optimization. The simulation results show that the strategy can adjust its kinetic model dynamically and overcome the instability of fed-batch process effectively. Run-to-run strategy with SEC-PSO provides an effective method for optimization of fed-batch fermentation process.展开更多
In order to improve the yield of β-mannase and to investigate the rules of fermentation production, a high-yield β-mannase producing strain, Bacillus licheniformis HDYM-04, was used to investigate the kinetics model...In order to improve the yield of β-mannase and to investigate the rules of fermentation production, a high-yield β-mannase producing strain, Bacillus licheniformis HDYM-04, was used to investigate the kinetics models based on the optimal fermentation conditions： HDYM-04 strain was fermented at 37℃ for 30 h with agitation speed at 300 r/min and aeration rate at 3 L/min in a 5 L fermenter, the initial addition amount of konjac flour was 2%（w/v）, the initial pH of medium was 8.0, and the inoculum concentration was 6.7%（v/v）. Three batch fermentation kinetic models were established （cell growth kinetic model, substrate consumption kinetic model, product formation kinetic model） bases on Logistic and Luedeking-Piret equations. To be specific, cell growth kinetic model was dX/dt =0.431X （1- X/ 15.522 ）, substrate consumption kinetic model was -ds/dt =1.11 dX/dt ＋0.000 2 dP/dt ＋0.000 8X, and product formation kinetic model was dP/dt=133.1 dX ＋222.87X. The correlation coefficients R^2 of the three equations were 0.990 21, 0.989 08 and 0.988 12, respectively, which indicated a good correlation between experimental values and models. Therefore, the three equations could be used to describe the processes of cell growth, enzyme synthesis and substrate consumption during batch fermentation using B. licheniformis strain HDYM-04. The establishment of batch fermentation kinetic models （cell growth kinetic model, substrate depletion kinetic model, product formation kinetic model） could lay the theoretical foundation and provide practical reference for the applica- tion of HDYM-04 in fermentation industry.展开更多
基金Supported by the National Natural Science Foundation of China （20676013）
文摘An iterative optimization strategy for fed-batch fermentation process is presented by combining a run-to-run optimization with swarm energy conservation particle swarm optimization (SEC-PSO). SEC-PSO, which is designed with the concept of energy conservation, can solve the problem of premature convergence frequently appeared in standard PSO algorithm by partitioning its population into several sub-swarms according to the energy of the swarm and is used in the optimization strategy for parameter identification and operation condition optimization. The run-to-run optimization exploits the repetitive nature of fed-batch processes in order to deal with the optimal problems of fed-batch fermentation process with inaccurate process model and unsteady process state. The kinetic model parameters, used in the operation condition optimization of the next run, are adjusted by calculating time-series data obtained from real fed-batch process in the run-to-run optimization. The simulation results show that the strategy can adjust its kinetic model dynamically and overcome the instability of fed-batch process effectively. Run-to-run strategy with SEC-PSO provides an effective method for optimization of fed-batch fermentation process.
基金Supported by Educational Commission of Heilongjiang Province of China(11551z011)
文摘In order to improve the yield of β-mannase and to investigate the rules of fermentation production, a high-yield β-mannase producing strain, Bacillus licheniformis HDYM-04, was used to investigate the kinetics models based on the optimal fermentation conditions： HDYM-04 strain was fermented at 37℃ for 30 h with agitation speed at 300 r/min and aeration rate at 3 L/min in a 5 L fermenter, the initial addition amount of konjac flour was 2%（w/v）, the initial pH of medium was 8.0, and the inoculum concentration was 6.7%（v/v）. Three batch fermentation kinetic models were established （cell growth kinetic model, substrate consumption kinetic model, product formation kinetic model） bases on Logistic and Luedeking-Piret equations. To be specific, cell growth kinetic model was dX/dt =0.431X （1- X/ 15.522 ）, substrate consumption kinetic model was -ds/dt =1.11 dX/dt ＋0.000 2 dP/dt ＋0.000 8X, and product formation kinetic model was dP/dt=133.1 dX ＋222.87X. The correlation coefficients R^2 of the three equations were 0.990 21, 0.989 08 and 0.988 12, respectively, which indicated a good correlation between experimental values and models. Therefore, the three equations could be used to describe the processes of cell growth, enzyme synthesis and substrate consumption during batch fermentation using B. licheniformis strain HDYM-04. The establishment of batch fermentation kinetic models （cell growth kinetic model, substrate depletion kinetic model, product formation kinetic model） could lay the theoretical foundation and provide practical reference for the applica- tion of HDYM-04 in fermentation industry.
