Advanced control with semi-empirical and data based modelling for falling film evaporators
| dc.contributor.advisor | Steyn, W. H. | en_ZA |
| dc.contributor.advisor | Auret, Lidia | en_ZA |
| dc.contributor.author | Haasbroek, Adriaan Lodewicus | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. | en_ZA |
| dc.date.accessioned | 2013-02-26T10:49:24Z | en_ZA |
| dc.date.accessioned | 2013-03-15T07:39:34Z | |
| dc.date.available | 2013-02-26T10:49:24Z | en_ZA |
| dc.date.available | 2013-03-15T07:39:34Z | |
| dc.date.issued | 2013-03 | en_ZA |
| dc.description | Thesis (MSc)--Stellenbosch University, 2013. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: This work focussed on a local multiple chamber falling film evaporator (FFE). The FFE is currently under operator control and experiencing large amounts of lost production time due to excessive fouling. Furthermore, the product milk dry mass fraction (WP) is constantly off specification, negatively influencing product quality, while the first effect temperature (TE1) runs higher than the recommended 70°C (this is a main cause of fouling). A two month period of historical data were received with the aim to develop a controller that could outperform the operators by keeping both control variables, WP and TE1, at desired set points while also increasing throughput and maintaining product quality. Access to the local plant was not possible and as such available process data were cleaned and used to identify two data based models, transfer function and autoregressive with exogenous inputs (ARX) models, as well as a semi-empirical-model. The ARX model proved inadequate to predict TE1 trends, with an average TE1 correlation to historical data of 0.36, compared to 0.59 and 0.74 for the transfer function and semi-empirical-models respectively. Product dry mass correlations were similar between the models with the average correlations of 0.47, 0.53 and 0.51 for the semi-empirical, transfer function and ARX models respectively. Although the semi-empirical showed the lowest WP correlation, it was offset by the TE1 prediction advantage. Therefore, the semi-empirical model was selected for controller development and comparisons. The success of the semi-empirical model was in accordance with previous research [1] [2] [3], yet other studies have concluded that ARX modelling was more suited to FFE modelling [4]. Three controllers were developed, namely: a proportional and integral (PI) controller as base case, a linear quadratic regulator (LQR) as an optimal state space alternative and finally, to make full use of process knowledge, a predictive fuzzy logic controller (PFC). The PI controller was able to offer zero offset set point tracking, but could not adequately reject a feed dry mass (WF) disturbance (as proposed and reported by Winchester [5]). The LQR was combined with a Kalman estimator and used pre-delay states. In order to offer increased disturbance rejection, the feedback gains of the disturbance states were tuned individually. The altered LQR and PFC solutions proved to adequately reject all modelled disturbances and outperform a cascade controller designed by Bakker [6]. The maximum deviation in WP was a fractional increase of 0.007 for LQR and 0.005 for FPC, compared to 0.012 for PI and 0.0075 for the cascade controller [6] (WF disturbance fractional increase of 0.01). All the designed controllers managed to reduce the standard deviation of operator controlled WP and TE1 by at least 700% and 450%, respectively. The same level of reduction was seen for maximum control variable deviations (370%), the integral of the absolute error (300%) and the mean squared error (900%). All these performance metrics point to the controllers performing better than the operator based control. In order to prevent manipulated variable saturation and optimise the feed flow rate (F1), a fuzzy feed optimiser (FFO) was developed. The FFO focussed on maximising the available evaporative capacity of the FFE by optimising the motive steam pressure (PS), which supplied heat to the effects. By using the FFO for each controller the average feed flow rate was increased by 4.8% (±500kg/h) compared to the operator control. In addition to flow rate gain, the controllers kept TE1 below 70°C and WP on specification. As such, the overall product quality also increased as well as decreasing the down time due to less fouling. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Hierdie projek het op ‘n vallende film verdamper (VFV) gefokus. Die VFV word tans beheer deur operateurs en ondervind groot hoeveelhede verlore produksie tyd a.g.v oormatige aangroeisels. Die vorming van aangroeisels is grootliks te danke aan die eerste effek temperatuur (TE1) wat gereeld 70°C oorskrei. Die produk droë massa fraksie (WP) is ook telkens nie op die gewenste vlak nie, wat produk kwaliteit negatief beinvloed. Data, wat oor ‘n twee maand periode strek, was verkry met die doelstelling om ‘n beheerder te ontwerp wat beter sou vaar as die operateurs, deur beide WP en TE2 om ‘n nou stelpunt te beheer. Ter selfde tyd moet die ontwerpte beheerder die produksie tempo en produk kwaliteit verhoog. Geen toegang tot die plaaslikke VFV was moontlik nie, dus was die data skoongemaak en gebruik om twee data gebasseerde modelle te identifiseer, nl. oordragsfunksie en outoregressiwe met eksogene insette (ORX) modelle, asook ‘n semi-empiriese model. Die ORX model kon nie TE1 goed voorspel nie, met ‘n korrelasie faktor (tot die historiese data) van 0.36, vergeleke met die 0.59 en 0.74 van die oordragsfunksie en semi-empiriese modelle onderskeidelik. WP korrelasie faktore was meer konstant tussen die modelle, met waardes van 0.47, 0.53 en 0.51 vir die semi-empiriese, oordragsfunskie en ORX modelle onderskeidelik. Alhoewel die semi-empiriese model die laagste WP korrelasie vertoon het, was die tekortkoming vergoed deur die beter TE1 voorspelling. Gevolglik was die semi-empiriese model gebruik vir beheerder ontwerp en vergelyking. Die sukses van die semiempiriese model stem ooreen met vorige studies [1] [2] [3], tog het ander studies al bevind dat die ORX model beter gepas is vir die VFV proses [4]. Drie beheerders was ontwikkel, nl. ‘n proporsionele en integreerder (PI) beheerder as basis geval, ‘n liniêre kwadratiese reguleerder (LKR) as optimale toestands beheer alternatief en laastens ‘n voorspellende wasige logika beheerder (VWB) om volle gebruik van proseskennis te maak. Die PI beheerder kon foutlose volging van die stelpunte lewer, maar kon nie ‘n inset voer droë massa fraksie (WF) versteuring (soos voorgestel en weergegee deur Winchester [5]) na wense verwerp nie. Die LKR was saamgevoeg met ‘n Kalman afskatter en het gebruik gemaak van onvertraagde toestande. Die versteuringstoestande was individueel verstel om beter versteurings verweping te weeg te bring. Die aangepaste LKR en VWB kon beide die WF versteuring verwerp en het beter gevaar as ‘n kaskade beheer oplossing wat deur Bakker [6] ontwerp was. Die WP afwyking is beperk tot ‘n fraksie droë masse verandering van 0.007 vir LKR en 0.005 vir VWB, vergeleke met die afwykings van 0.012 vir die PI beheerder asook die 0.0075 van die kaskade beheerder [6]. Die ontwerpte beheerder kon ook die standaard afwyking van beide WP en TE1 met ten minste 700% en 450% onderskeidelik verminder. Soortgelyke verbeterings was gesien vir die maksimum beheer veranderlikke afwyking (370%), die integraal van die absolute fout (300%) en die gemiddelde fout (900%). Dus het die ontwerpte beheerders wesenlik verbeter op die operateur beheer. Ten einde om gemanipuleerde veranderlikke versadiging te voorkom, asook die voer vloei (V1) te optimiseer, was ‘n wasige logika optimiseerder (WVO) ontwerp. Die WVO het die beskikbare verdampingskapasiteit ten volle benut deur te sorg dat die stoom druk (PS), wat energie verskaf vir verdamping, ge-optimiseerd bly. ‘n Gemiddelde V1 stygging van 4.8% (±500kg/uur), vergeleke met operateur beheer, is waargeneem. Al die beheerders kon steeds die WP en TE1 stelpunte volg en dus TE1 onder 70°C hou (wat verminderde vormasie van aangroeisels tot gevolg gehad het). Daarom het die produk kwailiteit verhoog en die verlore produksie tyd verminder. | af |
| dc.format.extent | 178 p. : ill. | |
| dc.identifier.uri | http://hdl.handle.net/10019.1/80196 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Advanced control | en_ZA |
| dc.subject | Dairy evaporator | en_ZA |
| dc.subject | Falling film evaporator | en_ZA |
| dc.subject | Fuzzy feed optimiser | en_ZA |
| dc.subject | Dissertations -- Electronic engineering | en_ZA |
| dc.subject | Theses -- Electronic engineering | en_ZA |
| dc.title | Advanced control with semi-empirical and data based modelling for falling film evaporators | en_ZA |
| dc.type | Thesis | en_ZA |