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Software sensors for bioprocesses.

Ph Bogaerts¹, A Vande Wouwer

¹Université Libre de Bruxelles, Control Engineering and System Analysis Department, Av. F.-D. Roosevelt, 50 C.P.165/55 B-1050 Brussels, Belgium. Philippe.Bogaerts@ulb.ac.be

ISA Transactions

|October 30, 2003

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State estimation in bioprocesses is challenging due to limited sensor data. This review covers software sensor methods like extended Kalman filters for improved process monitoring and control.

Area of Science:

Biotechnology
Process Control
Chemical Engineering

Background:

State estimation is crucial for biotechnological processes.
Limited hardware sensor measurements hinder accurate process dynamics monitoring.
Software sensors offer a viable solution for unmeasured variables.

Purpose of the Study:

To review various software sensor design methods applicable to bioprocesses.
To highlight the utility of these methods in overcoming sensor limitations.
To provide a comprehensive overview for researchers and engineers.

Main Methods:

Extended Kalman Filters (EKF)
Receding-Horizon Observers (RHO)
Asymptotic Observers (AO)
Hybrid Observers (HO)

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Main Results:

These software sensor methods can be efficiently implemented in bioprocesses.
Simulations demonstrate the effectiveness of the reviewed techniques.
Real-life case studies validate the practical applicability of these observers.

Conclusions:

Software sensors are essential for effective state estimation in bioprocesses.
The reviewed methods provide robust solutions for monitoring and control.
Further application of these techniques can enhance bioprocess performance and understanding.