Title :
Knowledge-Based Approach to Adaptive Computer Control in Manufacturing Systems
Author :
Lingarkar, Ravi ; Liu, Li ; Elbestawi, M.A. ; Sinha, Naresh K.
Author_Institution :
McMaster University, Hamilton, Ontario L8S4L7
Abstract :
A knowledge-based system approach for designing an adaptive controller is introduced in this paper. 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 [3] are used for knowledge representation and rules of logic for reasoning. Frames are knowledge structures that provide inheritance and data encapsulation, thereby allowing structured implementation and also enhancing maintainability of programs. 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 that 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 microprocessor based computer running at 20MHz. The knowledge representation and the reasoning process is implemented in PROLOG, whereas the numerical algorithms are written in C.
Keywords :
Adaptive control; Computer aided manufacturing; Computer numerical control; Control systems; Force control; Knowledge representation; Manufacturing systems; Metalworking machines; Programmable control; Safety;
Conference_Titel :
American Control Conference, 1989
Conference_Location :
Pittsburgh, PA, USA