On-line optimal trajectory control for a fermentation process using multi-linear models

Azimzadeh, F.; Galán, Omar; Romagnoli, JA

doi:10.1016/s0098-1354(00)00629-3

Cited by 24 publications

(9 citation statements)

References 8 publications

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“…For such LTI (Linear TimeInvariant) models, powerful controller design and analysis techniques exist. The use of such LTI models for the design of a controller for a nonlinear, complex system can be very effective, as is shown in, among others [27,28]. Furthermore, the strategy to arrive at the desired design model has to be straightforward and as general as possible, to make it attractive for other combinations of the crash and dummy and for other inputs and outputs.…”

Section: Modeling For Controller Designmentioning

confidence: 99%

Feedback control of occupant motion during a crash

Hesseling

Steinbuch

Veldpaus

et al. 2006

International Journal of Crashworthiness

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Passive in-vehicle safety systems such as the air bag and the belt restrain the occupant during a crash. However, often their behavior is not optimal in terms of occupant injuries. This paper discusses an approach to design an ideal restraint system. The problem is formulated as a feedback tracking problem with the objective to force the controlled variables, i.e., the acceleration of the head and the chest of the occupant, to follow a priori defined reference signals by simultaneous manipulation of the belt and the air bag. The reference signals have to reflect minimal injuries to the head, the chest, and the neck. More or less realistic numerical models of a crash test are far too complex to be used in control design processes. Therefore, a strategy is presented to derive simple, linear MIMO models. These models approximate the local dynamic behavior of the complex model and are suitable for control design. Analysis of the interactions in these simple models makes it plausible that the control design problem can be split into two separate tracking problems. Next, stabilizing low order controllers are designed using these models, and implemented in the closed loop system with the realistic numerical model. Results are presented, suggesting that feedback control with low order controllers is extremely effective as a basis for ideal restraint systems. Reductions of the adopted injury measures of at least 40% in comparison with the uncontrolled restraint system are achieved.

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Section: Modeling For Controller Designmentioning

confidence: 99%

Feedback control of occupant motion during a crash

Hesseling

Steinbuch

Veldpaus

et al. 2006

International Journal of Crashworthiness

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“…The asymmetrical constraints have been significantly considered in the model predictive control. In this framework, we can cite some works dealing with the bioprocesses control such as References where the input magnitude constraints in different ways have been solved.…”

Section: Introductionmentioning

confidence: 99%

Takagi‐Sugeno tracking control of a fermentation process with respect to asymmetric constraints

Mohamed

Karama

Khallouq

2019

Adaptive Control & Signal

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Summary This article deals with the tracking problem for nonlinear biological process with asymmetric constraints on the controller. Using the fuzzy logic Takagi‐Sugeno (TS), the nonlinear process is modeled by a fuzzy model and a parallel distributed compensation (PDC) controller with respect asymmetric constraints is designed. The main contribution of this work is to extend the available results, in the context of a TS formulation, for symmetrical constraints to asymmetrical ones. Hence, sufficient conditions are obtained for the first time, in terms of linear matrix inequalities (LMIs), for the existence of an asymmetrical constrained PDC controller. Moreover, fuzzy observer based controller with unmeasured premise variables is designed. The performance and effectiveness of the method are illustrated in simulation by considering a fermentation process.

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“…Azimzadeh et al (2001) characterized the reference profile using dissolved oxygen measurements to estimate the state of gluconic acid production 4 ; the dissolved oxygen exhibited several process stages that needed to be fulfilled to obtain the final product. Shamekh et al (2015) use an established temperature profile to evaluate PID control in a exothermic batch process 1 .…”

Section: Introductionmentioning

confidence: 99%

Reference Trajectory Design Using State Controllability for Batch Processes

Gómez-Pérez

Gómez

Álvarez

2015

Ind. Eng. Chem. Res.

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address: Carrera 80 #65-223, office: M3-100, Medellín, Colombia; zip code: 050041. Abstract:A proposal for the design of a reference trajectory for batch processes was developed, using set theory state controllability concepts. This proposal introduces the Available Control Action Set, which is an indicator of the state controllability and contains the largest amount of possible control actions that reach the desired final state. The volume of Available Control Action Sets can be maximized to improve the safety of batch processes while maintaining consistently high product quality. Thus a closed loop system has sufficient energy to reject disturbances, ensuring end-of-batch product quality. Case studies are presented to demonstrate the applicability of the approach to batch and semi-batch processes and to illustrate how the proposed method for the design of a reference trajectory for batch processes increases safe and robust operation.

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On-line optimal trajectory control for a fermentation process using multi-linear models

Cited by 24 publications

References 8 publications

Feedback control of occupant motion during a crash

Feedback control of occupant motion during a crash

Takagi‐Sugeno tracking control of a fermentation process with respect to asymmetric constraints

Reference Trajectory Design Using State Controllability for Batch Processes

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