Optimal Control of a MIMO Bioreactor System Using Direct Approach

In this paper, the optimal control of a continuous type bioreactor with multi-input-multi-output signals is presented for the two active phases: growth and stationary. The underlying criterion to be minimized generalizes the classic quadratic forms to address some crucial objectives in controlling t...

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Bibliographic Details
Published in:International journal of control, automation, and systems Vol. 19; no. 3; pp. 1159 - 1174
Main Authors: Simorgh, Abolfazl, Razminia, Abolhassan, Mobayen, Saleh, Baleanu, Dumitru
Format: Journal Article
Language:English
Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.03.2021
Springer Nature B.V
제어·로봇·시스템학회
Subjects:
Actuators
Bioreactors
Collocation methods
Control
Control methods
Cost function
Criteria
Engineering
Mechatronics
MIMO (control systems)
Nonlinear programming
Optimal control
Optimization
Quadratic forms
Quadratic programming
Regular Papers
Robotics
Trajectory control
제어계측공학
continuous bioreactor
optimal control
direct methods
nonlinear programming
Cheap control
ISSN:1598-6446, 2005-4092
Online Access:Get full text
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Summary:In this paper, the optimal control of a continuous type bioreactor with multi-input-multi-output signals is presented for the two active phases: growth and stationary. The underlying criterion to be minimized generalizes the classic quadratic forms to address some crucial objectives in controlling the bioreactor. In particular, the protection of actuators against fast switching in the controller output is considered by including a weighting term of the control signal derivatives. The direct optimal control approach is used to carry out the optimization in the presence of various limiting constraints. Direct methods are based on transcribing the infinite-dimensional problem to a finite-dimensional one. In this manuscript, direct single shooting and trapezoidal collocation methods are used for transcription, and the successive quadratic programming method is employed to solve the resulting nonlinear programming problem. It is shown that the trapezoidal method is an effective method for controlling the bioreactor in all the active phases, whereas the single shooting fails in dealing with the unstable one (i.e., growth). To analyze solutions in a more accurate manner, an auxiliary criterion is defined, and then the cheap control analysis is studied. The convergence to the lowest value of the auxiliary cost function and the effects on the optimal state and control trajectories are then examined by varying cheap parameters. Several numerical simulations support the presented theoretical formulation.
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http://link.springer.com/article/10.1007/s12555-020-0058-9
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-020-0058-9