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Feedback Control of a Recirculating Bioreactor with Electrophoretic Removal of Inhibitory Extracellular DNA

Antonio Spallone, Davide Fiore, Fabrizio Cartenì, Mario di Bernardo

Abstract

Extracellular DNA accumulation in recirculating bioprocesses inhibits microbial growth and reduces productivity. We consider a continuous bioreactor with a recirculating loop and an electrophoretic filtration unit for selective DNA removal, and develop a feedback control framework combining online state and parameter estimation via an Unscented Kalman Filter with two control strategies: an adaptive Model Predictive Controller that jointly optimizes dilution rate and filtration activation, and a simpler bang--bang filtration policy with lookup-table dilution rate selection. Closed-loop simulations under nominal and perturbed conditions show that the MPC strategy achieves significantly higher cumulative profit while keeping DNA concentration below the inhibition threshold.

Feedback Control of a Recirculating Bioreactor with Electrophoretic Removal of Inhibitory Extracellular DNA

Abstract

Extracellular DNA accumulation in recirculating bioprocesses inhibits microbial growth and reduces productivity. We consider a continuous bioreactor with a recirculating loop and an electrophoretic filtration unit for selective DNA removal, and develop a feedback control framework combining online state and parameter estimation via an Unscented Kalman Filter with two control strategies: an adaptive Model Predictive Controller that jointly optimizes dilution rate and filtration activation, and a simpler bang--bang filtration policy with lookup-table dilution rate selection. Closed-loop simulations under nominal and perturbed conditions show that the MPC strategy achieves significantly higher cumulative profit while keeping DNA concentration below the inhibition threshold.
Paper Structure (14 sections, 1 theorem, 19 equations, 3 figures, 2 tables)

This paper contains 14 sections, 1 theorem, 19 equations, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Problem formulation
  3. Parameter identification
  4. Problem Statement
  5. Online state and parameter estimation
  6. Augmented system observability
  7. Numerical validation of the UKF
  8. Control Design
  9. UKF+MPC
  10. UKF+lookup
  11. Simulation results
  12. Nominal closed-loop performance
  13. Robustness to parameter uncertainty
  14. Conclusions

Key Result

Proposition 1

Consider the augmented system eq:augmented_system with output $y_k = H_k \xi_k$, where only $b$ and $s$ are measured. Suppose that: Then the augmented system is locally weakly observable in the sense of Hermann--Krener HermannKrener1977 throughout the admissible operating region, and the parameter vector $\theta$ is locally identifiable from the available measurements.

Figures (3)

  • Figure 1: Schematic representation of the bioreactor with a recirculating loop (on the left) and an electrophoretic filtration unit (on the right).
  • Figure 2: Model fit against experimental data for biomass $b$, substrate $s$, and extracellular DNA $x$.
  • Figure 3: Closed-loop comparison between the UKF+MPC (solid blue lines) and the UKF+lookup (dashed orange lines strategies under nominal parameter conditions.

Theorems & Definitions (2)

  • Proposition 1: Local observability
  • proof