Generalization of Takagi-Sugeno Fuzzy Controller and its Application to Control of MMA Batch Polymerization Reactor

Abstract

In this research a generalization of Takagi-Sugeno fuzzy controllers is presented. In this generalization all or some of the inputs of the fuzzy controllers are fuzzy numbers. Also, it is proved that this generalization is well defined, which means that if the inputs of a generalized Takagi-Sugeno fuzzy controller are singleton fuzzy sets, then the generalized Takagi-Sugeno fuzzy controller will be reduced to a Takagi-Sugeno fuzzy controller. This controller was applied to temperature control of a methyl methacrylate (MMA) batch polymerization reactor, which uses jacket temperature error in addition to reactor temperature error. But the desired jacket temperature is affected by noise and disturbance. Therefore, there is uncertainty in the desired value of this variable. Fuzzy numbers are applied to model this uncertainty and a fuzzy trajectory was achieved for jacket desired temperature. After that an adaptation mechanism was designed. Experimental results present the fine performance of this controller in temperature control of solution polymerization of methyl methacrylate.

Hybrid intelligent control scheme of a polymerization kettle for ACR production

“…Shahrokhi and Fanaei [37] compared four controllers for nonlinear temperature control of a MMA batch suspension polymerization reactor. Nevertheless, both Shahrokhi and Fanaei [37] and Solgi et al [40] did not take time delay into account, which should not be ignored in temperature tuning of ACR polymerizaiton reactor.…”

“…Success of bench-scale implementation does not mean the same effect on the actual application. Solgi et al [40] presented a generalization of Takagi-Sugeno fuzzy controller and its application to control of methyl methacrylate (MMA) batch polymerization reactor. Shahrokhi and Fanaei [37] compared four controllers for nonlinear temperature control of a MMA batch suspension polymerization reactor.…”

Fuzzy Optimization Approach for the Synthesis of Polyesters and Their Nanocomposites in In-Situ Polycondensation Reactors

“…It was known that fuzzy controllers could be classified into two families: fuzzy model and fuzzy rules. In the past two decades, many manuscripts have been published about fuzzy theory applications in the controlling of the polymer chemical and its production process . Abony et al designed an adaptive Takagi–Sugeno fuzzy model as a process control for controlling the polymerization reaction which performed better than conventional controllers.…”

Projeto, montagem e instrumentação de um protótipo experimental de sistema de polimerização para o desenvolvimento e implementação de diferentes técnicas de controles inteligentes

“…Para o controle de propriedades dos polímeros, muitos algoritmos de controle avançados estão sendo utilizados em reatores de polimerização (MATEDDI, 2003;LIMA 2006;SOLGI ET AL. 2006;WAKABAYASHI, 2007).…”

“…Os sistemas neuro-fuzzy estão entre os sistemas híbridos mais pesquisados na atualidade. Muitos pesquisadores têm tentado integrar essas duas técnicas de modelagem para gerar um modelo híbrido que possa associar as vantagens de cada abordagem e minimizar suas deficiências (LEITE et al, 2011;KHAJEH et al, 2009;BURAGOHAIN e MAHANTA, 2008;EKPO e MUJTABA 2008;ERTUGRUL, 2008;SHEIKHZADEH et al, 2008;TAKAHASHI et al, 2008;ARRUDA, et al, 2007;TEIXEIRA et al, 2007, AL-HAJ et al, 2006MESA et al, 2006;NG e HUSSAIN, 2004;GALHARDO et al, 2009;PAGLIOSA, 2003;ZHANG, 2003;VIEIRA et al, 2003;ROCHA, 2003;CHENG e HUNG, 2002;PADILHA, 2001;VEGA, et al, 2000;).…”