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This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity.

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pela orientação, apoio, ensinamentos, conselhos e amizade. Ao Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) pelo apoio financeiro. Aos meus pais Jorge e Elisabeth e às minhas irmãs Adriana, Luciana e Fernanda pela formação do meu caráter e por todo o apoio com que sempre pude e sempre poderei contar. A família é essencial (inclusive para o fornecimento de cascas de abacaxi).Aos meus colegas de laboratório pelas contribuições, por compartilhar momentos de descontração e de dificuldades e que de uma forma ou de outra sempre tinham um palpite para ajudar: