Statistical fuzzy PID controller design

Neural-fuzzy control techniques have been employed in semiconductor equipment and manufacturing control applications. Many successful case studies have been reported to deal with nonlinear, time-varying systems. However, the problem of excessive control actions due to random disturbances or controller over-reactions to random noise has caused undesirable system responses which result in “under-and/or-over” the set-point. In this study, based on the statistical process control (SPC) idea, we introduce a SPC-fuzzy PID (proportional-integral-derivative) controller to cope with the random disturbances and to eliminate this problem. The SPC technique is being utilized as a supervisor to monitor the random disturbances and to identify the need of a control action against the random noise. This technique is applied to a IR (infra-red) heater component control which is one of the applications in the semiconductor manufacturing industry. The theoretical formulation of the IR heater, and the design of the SPC fuzzy PID controller is given in this study. The test results based on computer simulations are provided, which demonstrate the significant improvement over stand-alone fuzzy PID control