Use of causal knowledge in a real-time fuzzy logic controller

The establishment of expert control techniques and their actual industrial impact have been inhibited by the lack of a comprehensive design methodology. This paper summarizes the principal drawbacks limiting the development of a definitive methodology and addresses the key problem of acquisition of process/plant knowledge, clarifying first the types of knowledge. For a case-study, a real-time fuzzy rule-based controller employing causal knowledge is designed for the control of liquid level in a pilot plant. It is tested for closed-loop operation under different conditions, viz., set point change, noise disturbance, and structural (parametric) change. The results show that the fuzzy controller employing causal knowledge yields superior performance over a qualitative controller and the conventional PID controller implemented on the same plant and subjected to similar disturbances