کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4752019 | 1415987 | 2017 | 13 صفحه PDF | دانلود رایگان |
- A simplified model defining the maximum degradation rates as states is proposed.
- The model parameters and states are estimated by the Kalman filter.
- A terminal feasible set constraining predicted terminal states is proposed.
- Nonlinear MPC is designed to satisfy given constraints despite process disturbances.
This paper presents a nonlinear model predictive control approach for the anaerobic digestion process. A new model reduction strategy with estimation of the model parameters is proposed for the anaerobic digestion process. The reduced model is then used to predict future plant states in the nonlinear model predictive control. We develop a terminal feasible set to constrain terminal states in the prediction horizon, such that the controlled process beyond the horizon lies within a stable region and the predictive controller is recursively feasible. In addition, to make the predictive controller more practical, we design a predictive control algorithm that explicitly considers the influence of process disturbances and satisfies given constraints. Numerical simulations on the benchmark model ADM1 demonstrate the performance of the proposed method.
Journal: Biochemical Engineering Journal - Volume 128, 15 December 2017, Pages 63-75