Dynamic Model And Perturbation Control Of A Microorganism Reaction Process

With the rapid development of biotechnology, microbial reaction process occupies an important position in the national economy increasingly. Due to the complexity of microbial reaction mechanism, characteristics of nonlinear, time-varying, and uncertainty of the model etc, the study of microbial reaction process modeling is of great significance. On the other hand, when the microbial reaction process encounters more significant random disturbance or is affected by some uncertain factors, the classical control methods are difficult to achieve good results in the application of microbial reaction process. Therefore, to explore the appropriate modeling methods and optimal control strategy, then applying them to the microbial reaction process has important theoretical significance and practical significance. This work includes the following two parts:In the first part, two microbial reaction process non-structured models are established. In the first model, state feedback pulse control is applied to control the substrate concentration in the bioreactor medium. The dynamic analysis is carried out. In addition, by considering the biomass productivity as the objective, the process optimization is formulated and the optimal control level of substrate and the removal ratio of the reactor medium are obtained, which is helpful in improving the utilization of resources and biomass yield and quality. In the second model, a variable structure control is applied in modeling the bioprocess. By using Utkin equivalent control method, the existence and stability of normal, virtual, pseudo equilibria and tangent point are discussed. To implement the theoretical results, numerical simulations are carried out by using MATLAB software.In the second part, to keep the bioreactor at a stable steady state with maximum biomass productivity, the optimal control is applied. To deal with the chatting phenomenon on the singular arc, a sliding mode controller is proposed. The combined sliding mode optimal controller is applied to track the singular arc, and to maximize biomass production in the transient conditions. In addition, to consider that the uncertain factors in microbial continuous reaction process cause the system instability, interval type-2 fuzzy control is applied to control the process. Simulation results show that the control algorithm improves the dynamic performance of the control system effectively when the system parameter disturbance occurs.