A KNOWLEDGE-BASED SYSTEM USING FUZZY INFERENCE FOR SUPERVISORY CONTROL OF BIOPROCESSES

In this paper, a rule-based, real-time knowledge based system for bioprocess fault diagnosis and control is described. The system was designed to generate on-line advice for the operators and to supervise automatic control of bioprocesses, using biotechnical production of lactic acid as an example process. It consists of a real-time data acquisition and data processing system linked to a fuzzy expert system written in Smalltalk V/Mac. The expert knowledge was expressed in the form of a rule-based knowledge network, fuzzy membership functions and control strategies. The fuzzy expert system carries out on-line fault diagnosing on the basis of filtered specific rates calculated from process variable measurements, and provides suitable countermeasures to recover the process. Fault diagnosis was realized both by backward and forward chaining procedures. The system was constructed to allow three different control strategies (given here in Smalltalk syntax), change of Setpoint, FuzzyAnswer for each discovered fault, employing the fuzzy mean defuzzification method, and linguistic Advice to the operator. The system was successfully tested on-line with a laboratory scale process.