On-line estimation of glucose and biomass concentration in penicillin fermentation batch process using particle filter with constraint
In a penicillin fermentation process, substrate concentration and biomass concentration greatly influence the yield of the targeted product. However, there are few on-line sensors available to measure these variables in real-time. In this paper, a compact mechanism model is employed to simulate the fed-batch process, and a particle filter is introduced to estimate the substrate and biomass states. Particle filters are favorable to handle the state estimation problems with non-linearity, time-varying dynamics, and non-Gaussian distributions. In order to improve the quality of particles, optimization strategies are applied to deal with constraint issues. Furthermore, infrequent lab analyzed state information is incorporated into the estimation procedure and used to correct PF estimate. Simulation results show that the constrained PF approach has better estimation performance than extended Kalman filter in state estimation of this penicillin fermentation batch process.
Zhonggai Zhao Xinguang Shao Biao Huang Fei Liu
Institute of Automation, Jiangnan University, Wuxi, China, 214122. Department of Chemical and Materials Engineering, University of Alberta,Edmonton, AB, Canada, T6G 2G
国际会议
2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)
杭州
英文
391-396
2011-05-01（万方平台首次上网日期，不代表论文的发表时间）