Condenser and deaerator control using fuzzy-neural technique

الملخص EN

A model reference adaptive control of condenser and deaerator of steam power plant is presented.

A fuzzy-neural identification is constructed as an integral part of the fuzzy-neural controller.

Both forward and inverse identification is presented.

In the controller implementation, the indirect controller with propagating the error through the fuzzy-neural identifier based on Back Propagating Through Time (BPTT) learning algorithm as well as inverse control structure are proposed.

Simulation results are achieved using Multi Input-Multi output (MIMO) type of fuzzy-neural network.

Robustness of the plant is detected by including several tests and observations.