Solution to the Shell Standard Control Problem

Cuthrell, J.E.; Rivera, Delgado; Schmidt, Walter; Vegeais, J.A.

doi:10.1016/b978-0-409-90186-3.50010-0

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…The results (eg.. Fig. 8) showed that the new controller provided controller performance that compared well to the best QDMC solution [51] for the same problem.…”

Section: Ii22 Process Identification and Controller Design For Multmentioning

confidence: 66%

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

1991

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The results of the research caIried out from June 1989 through December 1991 and supported by the Department of Energy have been reported in a series of research papers, conference presentations, short courses, and seminars. These are listed in detail in section II.4 below. Several additional papers are in preparation. In this renewal proposal, it is impossible to provide a detailed account of ali the numerous developments and results obtained during the last 21/2 years. However, we are providing separately a report including reprints and preprints of ali publications. Thus in what follows, we shall only summarize the highlights of our work to date. ti.1 RESILIENT DESIGN AND CONTROL OF CHEMICAL REACTORS

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“…The results (eg.. Fig. 8) showed that the new controller provided controller performance that compared well to the best QDMC solution [51] for the same problem.…”

Section: Ii22 Process Identification and Controller Design For Multmentioning

confidence: 66%

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

1991

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“…Fig. 8) showed that the new controller provided controller performance that compared well to the best QDMC solution [51] for the same problem.…”

Section: Ii22 Process Identification and Controller Design For Multivariable Systemsmentioning

confidence: 71%

[New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries]

1991

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The results of the research caIried out from June 1989 through December 1991 and supported by the Department of Energy have been reported in a series of research papers, conference presentations, short courses, and seminars.These are listed in detail in section II.4 below. Several additional papers are in preparation.In this renewal proposal, it is impossible to provide a detailed account of ali the numerous developments and results obtained during the last 21/2 years. However, we are providing separately a report including reprints and preprints of ali publications.Thus in what follows, we shall only summarize the highlights of our work to date. ti.1 RESILIENT DESIGN AND CONTROL OF CHEMICAL REACTORS

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“…Nesta abordagem, a equação de previsão deve ser afim em relação ao vetor que representa a incerteza nos parâmetros para permitir a solução numérica do problema de otimização. Algoritmos utilizando modelos de resposta ao impulso e ao degrau com coeficientes incertos foram desenvolvidos para o controle do processo benchmark Shell, como por exemplo, o descrito em (Cuthrell et al, 1989;Biegler, 1989). A utilização de modelos ARIMAX para a modelagem de processos incertos neste contexto de RMBPC é descrita em (Gutierrez and Camacho, 1995).…”

Section: Modelos Utilizados Em Con-trole Preditivounclassified

Identificação e controle de processos via desenvolvimentos em séries ortonormais. Parte B: controle preditivo

Oliveira

Campello²,

Amaral

2007

Sba Controle & Automação

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O presente artigo aborda o problema da seleção da estrutura de modelos em algoritmos de controle preditivo para sistemas monovariáveis. Neste sentido, apresenta a utilização de modelos com estrutura dinâmica desenvolvida através de bases de funções ortonormais, como as funções de Laguerre, Kautz ou funções ortonormais generalizadas. Os principais aspectos relacionados com esta classe de modelos no contexto de controladores preditivos lineares com restrições terminais, não lineares e robusto são discutidos e uma revisão bibliográfica é apresentada. O desempenho de malha fechada das estratégias analisadas é ilustrado através de dois casos de estudo envolvendo uma incubadora para recém nascidos e um processo simulado de polimerização isotérmica.
This paper presents an overview about predictive control schemes based on orthonormal basis function models. Different predictive control schemes based on such models are discussed, namely, linear controllers with terminal (stabilizing) constraints, robust controllers, and non-linear controllers. The discussions comprise a broad bibliographical survey on the subject as well as two case studies involving a simulated dynamic system and a real process

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Solution to the Shell Standard Control Problem

Cited by 5 publications

References 5 publications

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

(New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries)

[New process modeling, design and control strategies for energy efficiency, high product quality and improved productivity in the process industries]

Identificação e controle de processos via desenvolvimentos em séries ortonormais. Parte B: controle preditivo

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