Configurable Platform for Optimal-Setting Control of Grinding Processes

For grinding processes, optimal-setting control (OSC) is becoming a hot topic. However, there is no configurable platform to assist researchers and engineers to design such a controller. This paper proposes a novel software platform named OSC to address this problem. The major superiority is that the platform not only provides a configurable environment by developing a powerful controller design tool and a Petri net model to schedule algorithm modules for parallel computation but also integrates several mainstream intelligent and data-driven algorithms (e.g., case based reasoning, fuzzy logic, and neural network) within a unified framework. The overall framework and key technologies are introduced in detail. Using a hardware-in-the-loop experiment system, the platform is verified and validated through a case of application where an intelligent optimal-setting controller is developed for a classical grinding process.