Gadkar Kapil G, Doyle Francis J, Crowley Timothy J, Varner Jeffrey D
Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California 93106, USA.
Biotechnol Prog. 2003 Sep-Oct;19(5):1487-97. doi: 10.1021/bp025776d.
The control of poly-beta-hydroxybutyrate (PHB) productivity in a continuous bioreactor with cell recycle is studied by simulation. A cybernetic model of PHB synthesis in Alcaligenes eutrophus is developed. Model parameters are identified using experimental data, and simulation results are presented. The model is interfaced to a multirate model predictive control (MPC) algorithm. PHB productivity and concentration are controlled by manipulating dilution rate and recycle ratio. Unmeasured time varying disturbances are imposed to study regulatory control performance, including unreachable setpoints. With proper controller tuning, the nonlinear MPC algorithm can track productivity and concentration setpoints despite a change in the sign of PHB productivity gain with respect to dilution rate. It is shown that the nonlinear MPC algorithm is able to track the maximum achievable productivity for unreachable setpoints under significant process/model mismatch. The impact of model uncertainty upon controller performance is explored. The multirate MPC algorithm is tested using three controllers employing models that vary in complexity of regulation. It is shown that controller performance deteriorates as a function of decreasing biological complexity.
通过模拟研究了在具有细胞循环的连续生物反应器中聚β-羟基丁酸酯(PHB)生产率的控制。建立了产碱杆菌中PHB合成的控制论模型。使用实验数据确定模型参数,并给出了模拟结果。该模型与多速率模型预测控制(MPC)算法相结合。通过调节稀释率和循环比来控制PHB的生产率和浓度。施加未测量的时变干扰以研究调节控制性能,包括无法达到的设定点。通过适当的控制器调整,尽管PHB生产率增益相对于稀释率的符号发生了变化,非线性MPC算法仍可以跟踪生产率和浓度设定点。结果表明,在存在显著过程/模型失配的情况下,非线性MPC算法能够跟踪无法达到的设定点的最大可实现生产率。探讨了模型不确定性对控制器性能的影响。使用三个采用调节复杂性不同的模型的控制器对多速率MPC算法进行了测试。结果表明,控制器性能随着生物复杂性的降低而恶化。