Knowledge-based adaptive computer control in manufacturing systems: A case study

A knowledge-based system approach for designing an adaptive controller is introduced. The proposed scheme has been used successfully in designing a self-tuning controller for force regulation in a computer numerically controlled (CNC) milling machine. In this scheme, frames are used for knowledge representation and rules of logic for reasoning. This synergistic combination of frames and rules provides an ideal environment for intelligent control. As a consequence of representing knowledge in frames, the large amount of ‘safety net’ of logics, which goes along with most conventionally designed adaptive controllers to ensure safe operation, is considerably reduced. Procedural attachments to the slots in the frame which behave as daemons replace the ‘safety net’ in the knowledge-based controller. The self-tuning controller for the CNC milling machine is implemented on a 32-bit micro-processor-based computer running at 20MHz. The knowledge representation and the reasoning process is implemented in Prolog, whereas the numerical algorithms are written in C. Simulations and experimental results are provided to demonstrate the usefulness of this approach.