A PID-Knowledge-Based System for Nonlinear Process Control

Abstract

An object-orientated knowledge-based management system (KBMS) architecture based on the concept of proportional-integral-differential (PID) control with self-learning capabilities is proposed for the high level control of complex systems. The architecture comprises: an enhanced KBS with tight coupling to a deductive database which allows both bottom-up and breadthwise search strategies to be implemented in an optimal combination. This management system selects both the set-point and the independently controllable variables; the independent variables can then be modified by an inductive process. The resultant system utilises experimental data for the tasking and control of a CO₂ laser manufacturing system.