Model Reference based Supervisory Fuzzy Logic Controller for Process Control

M. Adb El-Geliel and M.A. El-Khazendar (Egypt)


Normalized fuzzy controller, supervisor fuzzy controller, scaling factor tuning, and DCS systems.


In this paper, the designed schemes for a two Mamdani fuzzy controllers, employing the scaling factor tuning are proposed. The first fuzzy logic controller, is a normalized controller used to control the system, the tuning for its input and output-scaling factors is done through the second fuzzy controller (the supervisory controller) used to appropriately determine the control signal of the fuzzy controllers. The supervisory fuzzy controller tunes the normalized fuzzy controller based on the model reference adaptive control technique. The great advantage of the proposed method is that, a supervisor as a fuzzy controller to tune the scaling factor of a normalized fuzzy controller can be used to supervise any standard controller (with fixed parameters). This may be applied to control any process in the distributed control systems (DCS). The normalized fuzzy controller and the supervisory fuzzy controller are organized with specific experience information about the controlled systems. Finally, the proposed fuzzy controllers are applied practically to control a nonlinear thermal process; a comparison with scaling factor manual tuning, supervisor with step reference input and supervisor with desired model reference input is done to verify the effectiveness of the proposed design. The results shows that the last case the system is forced to follow the desired response

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