Smith Predictor-based Control of Systems with Time Delay

Smith Predictor is an effective method for control of processes in which the process time delay is long as it improves the performance of a PI controller. However, processes are susceptible to delay variation due to uncertainties and this predictive model does not guarantee plant robustness and stability due to the increase of negative phase lag. A temperature control experiment is conducted in a shell-tube Heat Exchanger Process Pilot Plant due to its time delay presence characteristic of interest. The process model in the form of transfer function is identified using Statistical Modelling with accuracy of 93.86%. A Smith Predictor-PI controller is developed using Matlab/Simulink to simulate the control of the temperature loop and results using performance indicators such as Integral Absolute Error (IAE) and Integral Square Error (ISE) show that it performs better than a PI controller

Process Control of Crushing Circuits

Kivenmurskaus on keskeinen osaprosessi kiviaineksen, metallien ja sementin tuotannossa. Murskaamalla tuotetut raaka-aineet muodostavat nykyaikaisen infrastruktuurimme perustan. Huolimatta merkittävästä roolistaan, kivenmurskaus on yksi harvoista teollisista prosesseista, jonka prosessinohjaus toteutetaan edelleen kokemusperäisesti, ilman luotettavaa mittaustietoa suoritettujen ohjaustoimien vaikutuksista. Nykykäytäntö altistaa murskausprosessit prosessivaihteluille ja –häiriöille, ja johtaa viime kädessä tehottomaan tuotantoon ja kapasiteetin vajaakäyttöön. Pääsyinä nykytilaan voidaan pitää murskausprosessien puutteellista anturointia ja tutkimustiedon puutetta korkeamman automaatioasteen tuomista hyödyistä. Tässä väitöskirjassa pyrittiin ratkaisemaan edellä mainittu ongelma automaattisen prosessinohjauksen avulla. Päätavoitteena oli kehittää säätömenetelmät murskauspiirin suorituskyvyn saattamiseksi lähelle parasta saavutettavissa olevaa tasoa. Tämä tutkimus perustuu mallipohjaiseen säädönsuunnittelumenetelmään. Systemaattinen suunnitteluprosessi alkoi säätötavoitteiden määrittelystä ja dynaamisten prosessimallien kehittämisestä. Kehitettyjen prosessimallien avulla luotiin säätötavoitteet täyttävä säätöstrategia ja viritettiin strategian vaatimat prosessisäätimet. Lopuksi simulointimallien avulla kehitetty ja testattu säätöstrategia implementoitiin osaksi laitoksen automaatiojärjestelmää ja sen suorituskyky arvioitiin täyden mittakaavan prosessikokeiden avulla. Tämä väitöskirja on osoittanut, että murskauspiirin tehokas ja tarkoituksenmukainen toiminta vaatii eri kahden säätötavan toteuttamista: massataseen säätö ja hienonnusmäärän säätö. Massatasesäädön tavoitteena on varmistaa 100 % käyttöaste murskauspiirin pullonkaulassa. Hienonnusmäärän säätö varmistaa halutun murskaimen tuotemateriaalin partikkelikokojakauman. Kehitetyt hienonnusmäärän säätömenetelmät perustuvat itseoptimoituvaan säätötapaan, joka mahdollistaa likimain optimaalisen suorituskyvyn käyttämällä säätimessä vakio-asetusarvoa. Kun tämä asetusarvo valitaan optimaalisesti, mahdollistaa esitelty ohjausstrategia parhaan saavutettavissa olevan murskauspiirin suorituskyvyn. Työn merkittävä tunnuspiirre on erityisen kattava empiria. Kehitetyt menetelmät testattiin kattavasti useissa erilaisissa tuotantoskenaarioissa ja prosessikonfiguraatioissa. Täyden mittakaavan prosessikokeiden tulokset vastasivat hyvin lähelle simulaatioilla saatuja tuloksia. Tämä väitöskirja on merkittävä edistysaskel murskausprosessien säädössä. Työn tuloksena kehitetyt mittaus- ja säätötavat mahdollistavat tehokkaamman ja tarkoituksenmukaisemman raaka-ainetuotannon. Työn tuloksilla voidaan olettaa olevan merkittävä vaikutus siihen, miten ja millä tavoin murskausprosesseja ohjataan tulevaisuudessa. Työssä kehitetyn murskauspiirin automaattisen säätöstrategian voidaan olettaa toimivan perustana tulevaisuuden murskausprosessien prosessiautomaatio-toteutuksille.Crushing is an essential high-volume processing stage in the production of aggregates, metals and cement. Crushed products form the basis of our modern infrastructure and therefore play a major role in the economic growth and welfare. Despite its significant role in society, crushing is one of the few remaining industrial processes that is currently being operated using belief-based manual control without the possibility to quantify the consequences of performed control actions. This practice makes crushing processes vulnerable to process variation and exposes them to inefficient production and capacity underutilization. The aim of this thesis is to address this deficiency by bridging the gap between theoretically possible and realized crushing circuit performance, by means of automatic process control. This thesis covers the entire model-based control system design procedure – from the formulation of control objectives and development of dynamic process model(s), through the development of control strategy, to the control system implementation and performance evaluation – for crushing circuits. Research has led to significant advances within crushing process measurement and control. Developed methods have been rigorously tested in various production scenarios and circuit flowsheets, using both dynamic simulations and full-scale experiments. Experiments revealed expected behavior with a significant increase in performance. The results have shown that the efficient operation of a crushing circuit requires addressing two control tasks: mass balance control and size reduction control. The objective of mass balance control is to guarantee 100 percent circuit utilization, whereas size reduction control ensures the desired degree of size reduction. The ideal degree of size reduction is determined empirically to maximize the value of the used KPI. The developed control strategy delivers near-maximum circuit performance. This thesis represents a major leap forward in the area of process control of crushing circuits. It has opened entirely new possibilities by making it possible to quantify the instantaneous performance of crushing circuits and by introducing the ability to ensure consistent and efficient long-term production. These major breakthroughs can have a significant impact on how crushing plants will be operated in the future. Developed standard control practice can be expected to serve as a basis for future control system implementations of industrial crushing circuits

Contribuições ao controle de variância mínima generalizado: abordagem de projeto no espaço de estados

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Automação e SistemasNeste trabalho, o controlador de Variância Mínima Generalizado, GMV, é desenvolvido no domínio de representações no espaço de estados, beneficiando-se de uma equivalência de seu preditor de variância mínima com uma solução particular do Filtro de Kalman, a qual caracteriza uma atraente abordagem por evitar a solução da equação de Diophantine. O procedimento de projeto se baseia na característica de que a estrutura do controlador é herdada do modelo de projeto, onde variáveis de estado estimadas, com significado ou comportamento físico compreensível, entram na síntese de uma lei de controle por realimentação de estados estimados. A complexidade da estrutura do controlador é então ditada pela complexidade do modelo de projeto, mas o procedimento de sintonia, mesmo para sistemas multivariáveis e com múltiplos atrasos assíncronos, é factível de ser executado e implementado. A idéia usada no GMV via realimentação de estados está focada no controlador GMV de ordem mínima, o qual é sintonizado por um único parâmetro escalar que pondera a energia empregada no sinal de controle. Mas como o conceito de variáveis de estado é introduzido, a lei de controle resultante é uma composição de diversos GMVs de ordem mínima, um para cada variável de estado considerada no problema. A base teórica para o desenvolvimento desse controlador por realimentação de estados estimados é um novo procedimento de projeto de controle GMV no espaço de estados, conhecido como GMVSS. Este procedimento difere do original, de Clarke e Gawthrop, via funções de transferência, mas fornecendo exatamente os mesmos resultados. A contribuição mais significativa do GMVSS é a simplicidade de obtenção do preditor devido a ausência da equação de Diophantine no procedimento de projeto. A Diophantine é resolvida indiretamente e de maneira natural pela própria formulação do problema, a partir do Filtro de Kalman obtido de uma representação ARMAX no espaço de estados, dispensando também a solução da equação a diferenças de Riccati para calcular o ganho de Kalman. A união dos resultados do GMVSS com a abordagem por realimentação de estados estimados, abre novas perspectivas de projeto de controle GMV com filtragem de Kalman de forma intrínseca e sintonia do controlador baseada em GMVs de ordem mínima operando paralelamente como em uma topologia de controle de múltiplas malhas.In this work, the Generalized Minimum Variance controller, GMV, is developed within the state space framework, benefiting from an equivalence of its minimum variance predictor with a particular solution of the Kalman Filter, which characterizes an attractive approach since it avoids the Diophantine equation solution. The design procedure is based on the characteristic that the controller structure is inherited from the design model, where estimated state variables, with comprehensible physical meaning or behavior, come into play in the synthesis of a state-feedback control law. The complexity of the controller structure is then dictated by the complexity of the design model, but the tuning procedure, even for asynchronous multi-delayed multivariable systems, is feasible to be handled with a certain degree of simplicity. The main idea behind the state-feedback GMV controller is focused on the minimal order GMV controller, which is tuned by a single scalar parameter that weights the energy employed on the control signal. Since the state variable concept is introduced, the produced control law is the composition of several minimal order GMVs, each one to every state variable considered in the problem. The theoretical base used in the development of the estimated state-feedback controller is a new GMV state space design procedure, known as GMVSS. This procedure differs from the original transfer function method, of Clarke and Gawthrop, but matching exactly the same results. The most significant contribution of GMVSS is the simplicity of the predictor design, since it avoids the Diophantine equation solution. The Diophantine is indirectly solved in a natural way by the problem formulation itself, from a Kalman Filter obtained from an ARMAX state space representation, that also dismisses the Riccati difference equation solution to derive the Kalman gain. By putting together the GMVSS and the state-feedback approach results, leads to new design perspectives of GMV control with intrinsic Kalman filtering techniques and tuning of minimal order GMVs operating as if in a multi-loop control topology