Application of Feedback Linearization to Bioreactor Control
ABSTRACT This paper presents the procedures and results of Using the input-output linearization technique in the design of a controller for a generic nonlinear continuous bioreactor. Of special interest is the existence of singular points which renders direct application of the input-output linearization theory infeasible. In this paper, we present a modified scheme which allows us to approximately extend the input-output linearization technique across the singular points. The feasibility and effectiveness of the proposed method are demonstrated through computer simulation. This modified method provides a more intuitive insight into the nonlinear system control.
- SourceAvailable from: uni-stuttgart.deNichtlineare Regelung : Methoden, Werkzeuge, Anwendungen; VDI/VDE-GMA-Aussprachetag 13./14. 5. 1993, Langen, 209-234 (1993).
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ABSTRACT: In this paper, the potential difficulties with the application of exact linearization technique to a class of continuous bioreactors are examined. We concentrate on input-output linearization since the input-state linearization can be viewed as a special case of input-output linearization. Input-state linearization can have all the same problems except unstable zero dynamics. Various control structures are compared. We emphasize on the analysis of zero dynamics, singular points and disturbance decoupling property. We introduce the process and the control objective. We briefly review the exact input-output linearization theory. We study single loop control structures with the dilution rate D, the single loop control with feed substrate concentration, and the multivariable controlControl Applications, 1993., Second IEEE Conference on; 10/1993
Conference Paper: Optimization approach to controlling constrained nonlinear systems[Show abstract] [Hide abstract]
ABSTRACT: The authors discuss the results of using the input-output geometric transformation method in the development of an efficient controller for nonlinear systems with constraints, while being easy and intuitive to tune and requiring minimal computational effort. While dynamic matrix control (DMC) and quadratic DMC (QDM-C) have been successfully applied in optimal control of industrial processes, they are restricted to linear/near-linear processes. An approach combining the transformation method with DMC for nonlinear systems with constraints that require low computational effort is reported. Using input-output linearization, a pseudolinear model of the system is derived that is valid for the entire region of operation. DMC is designed on this system, ignoring constraints. The DMC-computed input is checked for constraint violation, and a pointwise optimal feasible input is generated if such violation occurs. The performance of the proposed control scheme is demonstrated via simulation of two processes: a continuous stirred tank bioreactor (CSTBR), and an exothermic continuous stirred tank reactor (CSTR)Decision and Control, 1992., Proceedings of the 31st IEEE Conference on; 02/1992