Method and system for gas turbine engine simulation using adaptive Kalman filter

A method for simulating an actual gas turbine comprising:

• a. sensing values of a plurality of input operating parameters of an actual gas turbine;
• b. applying the sensed values of the first operating parameters to a model of the gas turbine that generates predicted values of a plurality of primary output operating parameters;
• c. determining difference values by comparing the predicted values to sensed primary output operating parameters of the actual operating gas turbine;
• d. applying a Kalman filter gain matrix to the difference values, wherein the Kalman filter gain matrix is generated or modified during operation of the actual gas turbine and wherein generating the Kalman filter gain matrix includes applying the sensed values of the plurality of first operating parameters and perturbated difference values to generate correction factors;
• e. applying the correction factors to adjust the model of the gas turbine, wherein the model generates at least one of predicted operating parameter applied to control the actual gas turbine;
• f. after step (e) removing one of the difference values and repeating steps (a) through (e).

A control and modeling system for simulating an operating gas turbine comprising:

• sensors generating sensed values of a plurality of first operating parameters of the operating gas turbine;
• a controller including a mathematical model of the operating gas turbine receiving the sensed values of the first operating parameters and a plurality of correction factors, wherein the model generates a plurality of predicted second operating parameters;
• a comparator determining difference values between the predicted second operating parameters and corresponding sensed operation parameters of the operating gas turbine, and
• said controller further generates and modifies during operation of the operating gas turbine an adaptive Kalman filter gain matrix to be applied to the difference values to generate the correction factors, wherein the Kalman filter gain matrix is generated by applying the sensed values of the plurality of first operating parameters and a series of perturbated values of the predicted second operating parameters.