Review of Tuning Methods of DMC and Performance Evaluation with PID Algorithms on a FOPDT Model

Kokate, Rajendra D.; Waghmare, L. M.; Deshmukh, Samruddhi

doi:10.1109/artcom.2010.109

Cited by 14 publications

(12 citation statements)

References 4 publications

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“…The design of PID controller [8] is the design of the three important parameters. According to the FOPDT model related to PID controller design problems for this kind of controlled object, in 1942, the empirical formula proposed by Nichols and Ziegler has the greatest impact, so that in many projects it is still in use.…”

Section: Pid Controller Parameters Optimization and Effectmentioning

confidence: 99%

Electric tracing system temperature control of submarine heavy oil pipeline based on genetic algorithm

Ding¹,

Zhang²

2016

Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

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In order to optimize the heating dynamic response of heavy oil in the submarine pipeline, the control system of the pipeline electric current tracing system is designed. Firstly, the mathematical model of electric current tracing system for heavy oil pipeline is established based on mechanism modeling method. Aims at the controlled object with First Order Plus Dead Time (FOPDT) model, temperature is controlled with the most widely used PID controller in industrial process control. Secondly, a variety of tuning methods for controller parameters are discussed. Finally, the temperature control method based on genetic algorithm tuning is established, and comparisons are drawn by MATLAB simulation. The results show that the temperature overshoot of PID temperature control method based on genetic algorithm is smaller, and the time for heating to target temperature is also significantly reduced. Therefore, PID temperature control method based on genetic algorithm can shorten the tuning time for parameters significantly, it has the higher heating efficiency with less energy cost, furthermore, and it can well meet the needs of heating system control.

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Section: Pid Controller Parameters Optimization and Effectmentioning

confidence: 99%

Electric tracing system temperature control of submarine heavy oil pipeline based on genetic algorithm

Ding¹,

Zhang²

2016

Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

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“…Em (Qin and Badgwell, 2003) e apresentada uma extensa revisão do DMC com aplicações industriais e em (Kokate et al, 2010) uma revisão da literatura quanto a métodos de sintonia do DMC para processos SISO. Dentre os métodos de sintonia automática (autotuning) se destaca o de Shridhar and Cooper (1997) por sua facilidade de uso a partir de um modelo firstorder-plus-dead-time (FOPDT).…”

Section: Introductionunclassified

Estratégia avançada de sintonia para controle por matriz dinâmica com aplicação não-linear

Jeronymo¹,

Coelho²

2013

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Abstract-In this paper an autotuning method for Dynamic Matrix Control (DMC) is presented with application to single-input single-output (SISO) processes which can be approximated by a first-order-plus-dead-time model. In order to validate the method a non-linear control valve system described by a Wiener process is simulated. This process was identified by a Hammerstein model so DMC could perform non-linear control. The proposed tuning method has its performance compared to another method commonly found in literature, showing more conservative results regarding smoothness of the control action while maintaining adequate performance on settling time.Keywords-dynamic matrix control, non linear control, first-order-plus-dead-time, autotuning.Resumo-Neste trabalhoé apresentado um método de sintonia automática (autotuning) para o DMC com aplicação em processos SISO que possam ser aproximados por um modelo FOPDT. Para validação do métodó e simulado um sistema não-linear de válvula de controle descrito por um processo Wiener. Um processo Hammersteiné identificado a partir deste sistema para efetuar o controle não-linear pelo DMC. O método de sintonia proposto tem seu desempenho comparado com outro método popularmente encontrado na literatura, demonstrando resultados mais conservativos quanto a suavidade da ação de controle enquanto mantem bom desempenho relativo ao tempo de acomodação.Palavras-chave-controle por matriz dinâmica, controle não linear, FOPDT, sintonia automática. IntroduçãoO algoritmo do controle preditivo por matriz dinâmica (Dynamic Matrix Control -DMC) tem se mantido essencialmente o mesmo desde a sua concepção nos trabalhos originais por (C.R. and P. S., 2001;Cutler et al., 1982). As inovações nestá area do controle preditivo baseado em modelo são apresentadas fundamentalmente para dois problemas diferentes: i) a representação matemática do modelo, e ii) a sintonia de parâmetros, os horizontes e fator de supressão de movimento, do controlador.A sintonia de parâmetros do DMCé problemática já que não há maneira analítica exata para obtenção dos parâmetros que produzam a melhor resposta desejada. Em (Qin and Badgwell, 2003) e apresentada uma extensa revisão do DMC com aplicações industriais e em (Kokate et al., 2010) uma revisão da literatura quanto a métodos de sintonia do DMC para processos SISO. Dentre os métodos de sintonia automática (autotuning) se destaca o de Shridhar and Cooper (1997) por sua facilidade de uso a partir de um modelo firstorder-plus-dead-time (FOPDT).Neste trabalhoé apresentado um método de sintonia para o DMC considerando plantas que possam ser aproximadas por um modelo FOPDT. Inicialmente, parte-se de considerações de uma realização mínima do DMC para que seja possível efetuar uma análise do comportamento do sistema em malha fechada. Em seguida a sintoniaé expandida para melhor contemplar o modelo do processo, utilizando o tempo de resposta e atraso do tempo morto. Observa-se que esta sintonia expandidaé um híbrido da sintonia do fator de supressão de movimentos desta proposta ...

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“…It is also called objective function. It is the performance criterion for controller [6]. The controller will make plant to follow a particular reference trajectory with satisfying performance criterion.…”

Section: Cost Functionmentioning

confidence: 99%

“…In matrix-vector form, for a prediction horizon P and a control horizon of M steps yields: (6) Thus, the difference between the reference trajectory y r and the future prediction y P is:…”

Section: Derivation Of Dmc Algorithmmentioning

confidence: 99%

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Design of Unconstrained DMC to Improve the Distillate Product Purity of the Distillation Column

2016

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Abstract. This paper demonstrates the use of unconstrained Dynamic Matrix Control (DMC) to control the process transfer function with time delay. The selection of tuning parameter is challenging task in predictive control algorithm. The DMC scheme is designed and it is used here to control the process transfer function, First Order Plant with Dead Time (FOPDT) model. Here, one manipulated variable (reflux) and one controlled variable (distillate) is considered for the implementation. The algorithm significantly controls the reflux to improve the distillate product purity. The simulation is done using MATLAB m-file. Both servo and regulatory responses were obtained. The simulation result validates the effectiveness of the proposed algorithm.

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Review of Tuning Methods of DMC and Performance Evaluation with PID Algorithms on a FOPDT Model

Cited by 14 publications

References 4 publications

Electric tracing system temperature control of submarine heavy oil pipeline based on genetic algorithm

Electric tracing system temperature control of submarine heavy oil pipeline based on genetic algorithm

Estratégia avançada de sintonia para controle por matriz dinâmica com aplicação não-linear

Design of Unconstrained DMC to Improve the Distillate Product Purity of the Distillation Column

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