Object-oriented approach applied to ANFIS modeling and control of a distillation column

• We develop an indirect control scheme based on neurofuzzy approach.
• We use the ANFIS paradigm to modelling and control under the MODELICA environment.
• The MODELICA approach provides simplicity and flexibility during the controller design process.
• We highlight the application to dual composition control of a distillation column.
• The ANFIS control entails a step ahead as compared with conventional control.

Neurofuzzy networks are hybrid systems that combine neural networks with fuzzy systems, and the Adaptive Neuro-Fuzzy inference system (ANFIS) is a particular case in which a fuzzy system is implemented in the framework of an adaptive neural network. This neurofuzzy approach represents an effective structure to the modeling of plant dynamics, and the oriented-object programming environments offer an intuitive way to address this task. In this paper the MODELICA object-oriented environment has been applied to the ANFIS modeling and indirect control of the heavy and light product composition in a binary methanol-water distillation column by using the adaptive Levenberg–Marquardt approach. The results obtained demonstrate the potential of the adaptive ANFIS scheme under MODELICA for the dual control of composition both for changes in set points with null stationary error even when disturbances are present.