Identification of fuzzy controller for use with a falling-film evaporator

Lahtinen, Seppo

doi:10.1016/s0956-7135(01)00004-4

Cited by 18 publications

(9 citation statements)

References 20 publications

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“…The results show that this approach is more efficient than the use of classical trapezoidal membership functions. List of the applications on the four topics Representation of the descriptive sensory evaluation [20,22,28,31,39,57,62,[82][83][84]86] Indirect measurement Fuzzy rule basis Data-driven approaches: [12,13,17,23,49,76,79,91] Knowledge driven approaches: [11,36,55,59,93] Classification [2,[5][6][7]14,33,41,46,50,52,67,69,73,75] Diagnosis, supervision or control Data-driven approaches [4,25,29,32,[43][44][45]70,72,88,90] Knowled...…”

Section: Resultsmentioning

confidence: 99%

Fuzzy concepts applied to food product quality control: A review

Perrot

Ioannou²,

Allais

et al. 2006

Fuzzy Sets and Systems

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Section: Resultsmentioning

confidence: 99%

Fuzzy concepts applied to food product quality control: A review

Perrot

Ioannou²,

Allais

et al. 2006

Fuzzy Sets and Systems

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“…Haasbroek et al (2013) derived the semi-empirical model and tested the Linear Quadratic Regulator (LQR) to reject the disturbances. Lahtinen (2001) applied an intelligent control technique; that is, Takagi-Sugeno fuzzy inference system (T-S-FIS) based control to optimize the process recirculation of brix level and syrup flow in the equipment. Karimi et al (2007) used a cascade controller for a 3-effect MSE.…”

Section: Introductionmentioning

confidence: 99%

Modeling, simulation and control of the dynamics of a Heptads’ effect evaporator system used in the Kraft recovery processes

Verma

Mohammed

Mangal

et al. 2017

Transactions of the Institute of Measurement and Control

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This research article attempts to investigate the dynamic behavior of the heptads’ effect evaporator (HEE) used to concentrate the weak black liquor during the Kraft recovery process in a paper industry. In order to fully characterize the HEE unit, a complete understanding of its performance for steady state and transient conditions is required. For this purpose, a set of first order nonlinear differential equations have been developed for the backward feed flow configuration (BFFC) for an unsteady state. Further, the developed non-linear model is linearized and linear state space equations obtained. The dynamic response of the system in terms of vapor temperature and liquor concentration changes for different changes in input liquor flow rate has been investigated. The rise, delay and settling times for the temperature deviation from steady state have been found to be significantly less as compared with that for the concentration deviation. The results also indicate that each effect of HEE acts as an individual first order system. The placement of such first order systems in series makes both the liquor concentration and vapor temperatures response more sluggish progressively with each subsequent effect. Finally, a Cascade-PID control strategy has been implemented and shown to exhibit differentiated and improved dynamic performance of the HEE system versus open-loop dynamic response.

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“…In [1]- [3], the input-output linearization decoupling technique based on differential geometry was proposed for the forced-circulation system and the five-effect evaporation system. In [4] and [5], the multivariable supervisory control method and the fuzzy control technique were applied to the falling film evaporator system. In [6] and [7], a model predictive control method was applied to an evaporation system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Wang

Chai

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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Abstract-For the forced-circulation evaporation process of alumina production, the control objectives include maintaining the liquid level and fast tracking of the product density with respect to its setpoint. However, with the strong coupling between the level control and product density control loops and the process exhibits strong nonlinearities, conventional control strategies, such as proportional-integral-derivative and other linear control design, cannot achieve satisfactory control performance and meet production demands. By augmenting the forced-circulation evaporation system model with dynamics of its operating valves, a nonlinear adaptive decoupling switching control strategy is proposed. This control strategy includes a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller, and a switching mechanism. The linear adaptive decoupling controller is used to reduce the coupling between the two control loops. The neural-network-based nonlinear adaptive decoupling controller is employed to improve the transient performance and reduce the effects of the nonlinearities on the system, and the switching mechanism is introduced to guarantee the input-output stability of the closed-loop system. Simulation results show that the proposed method can decouple the loops effectively for the forced-circulation evaporation system and thus improve the evaporation efficiency.

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Identification of fuzzy controller for use with a falling-film evaporator

Cited by 18 publications

References 20 publications

Fuzzy concepts applied to food product quality control: A review

Fuzzy concepts applied to food product quality control: A review

Modeling, simulation and control of the dynamics of a Heptads’ effect evaporator system used in the Kraft recovery processes

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

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