Title :
Knowledge-based adaptive computer control in manufacturing systems: a case study
Author :
Lingarkar, Ravi ; Liu, Li ; Elbestawi, Mohamed A. ; Sinha, Naresh K.
Author_Institution :
Dept. of Electr. & Comput. Mech. Eng., McMaster Univ., Hamilton, Ont., Canada
Abstract :
A knowledge-based system approach for designing an adaptive controller is introduced. The 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 the environment for intelligent control. As a consequence of representing knowledge in frames, the large amount of logic that goes along with most conventionally designed adaptive controllers to ensure safe operation is considerably reduced. Procedural attachments to the slots in the frame replace the extra logic elements in the knowledge-based controller. The self-tuning controller for the CNC milling machine is implemented on a 32-b microprocessor-based computer running at 20 MHz. The knowledge representation and the reasoning process are implemented in Prolog, whereas the numerical algorithms are written in C. Simulations and experimental results are provided that demonstrate the usefulness of this approach
Keywords :
adaptive control; computerised numerical control; control system CAD; force control; knowledge based systems; knowledge representation; machining; manufacturing computer control; CNC; Prolog; adaptive controller; force regulation; intelligent control; knowledge representation; knowledge-based system; milling machine; self-tuning controller; Adaptive control; Computer aided manufacturing; Computer numerical control; Control systems; Force control; Knowledge representation; Logic; Manufacturing systems; Metalworking machines; Programmable control;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on