Advanced Control Decision Tree

This paper describes how to make advanced control choices when difficult processes need improvement. The decision-making process involves choosing between a rules-based approach and a model-based approach as well as weighing benefits and drawbacks, complexity and simplicity, investment and results. This paper will present briefly each solution: basic control, advanced regulatory control, model predictive control and expert systems such as fuzzy logic controllers and neural networks. Three examples are presented: ARC (Advanced Regulatory Control) on pH in a comminution circuit, MPC (Model Predictive Control) for combustible management and FLC (Fuzzy Logic Control) on a Semi Autogenous Mill. The article then proposes a decision tree for selecting the most appropriate approach. A table will compare usage, development, commissioning, maintenance and lifecycle costs for each approach. Finally, conclusions and suggestions will summarize the methodology.