Modelling and effective predictive control of gas turbine process

Model predictive controller is being used to control system such a chemical plants, oil refineries, food industry, automotive industry etc.. It is formulated as advanced method of process control. The main advantage of MPC method is that, it is solved as optimization problem. So the method tries to minimize the needed input to achieve desired output of the controlled system. The next advantage is that this optimization problem can be easily restricted. Different constraints can be applied to controlled system and it still can be controllable with the optimal input. Another source defines MPC as a linear algebra method for predicting the result of a sequence of control variable manipulations. Once the results of specific manipulations are predicted, the controller can then proceed with the sequence that produces the desired result. One can compare this controller method to "look ahead" in chess or other board games. In look ahead, you foresee what an action might yield sometime in the future using specific knowledge of the process (or game in the case of chess), and are thereby able to optimize your actions to select for the best long term outcome. MPC methods can prevent an occurrence with conventional PID controllers in which actions taken achieve short term goals, but end up very costly in the end. The proposed paper deals with the effective predictive control algorithm for the gas turbine on the base of real mathematical model which is obtain from measured I/O data. For the verification of the proposed MPC algorithm, the program system was created, which enables verification of control algorithm parameters. It can by effectively implemented using embedded microcontrollers or FPGA circuits.