Developing a Model of an Intelligent Control Technique on a Manufacturing Batching Process

Abstract

Complex control algorithms are applied to manufacturing systems for certain process requirements, according to product specifications. When implementing specific complex control algorithms, primary and secondary conditions affect each other, affecting the measuring and control processes. While complex control algorithms result in several benefits, problems associated with mathematical reasoning and time delays need to be considered for an intelligent decision-making control technique to optimise control of the manufacturing process. The research will derive a suitable control technique by means of an adaptive neuro-fuzzy inference system, to optimise the manufacturing process. The paper will discuss technical aspects, the experimental set-up and the design process. Completed research on industrial Siemens FuzzyControl++ design tool and current research on MatLab Fuzzy Logic Toolbox will form part of the discussion on the design process. The paper will conclude with a comparison of various analysis results in MatLab Fuzzy Logic Toolbox