Model-based machine learing control system and method for tuning power production emissions

A method, comprising:

• selecting a desired parameter of a machinery configured to produce power and to output emissions;
• selecting an emissions model configured to use the desired parameter as input and to output an emissions parameter;
• continuously tuning the emissions model during operations of the machinery via a tuning system to derive a setpoint via machine learning;
• adjusting the setpoint by applying a tuning bias, wherein the tuning bias is continuously updated via segmented linear regression;
• and
• controlling one or more actuators coupled to the machinery based on the adjusted setpoint.

A non-transitory, computer-readable medium comprising executable code comprising instructions configured to:

• select a desired parameter of a machinery configured to produce power and to output emissions;
• select an emissions model configured to use the desired parameter as input and to output an emissions parameter;
• continuously tune the emissions model during operations of the machinery via tuning system to derive a setpoint via machine learning;
• adjust the setpoint by applying a tuning bias, wherein the tuning bias is continuously updated via segmented linear regression;
• and
• control one or more actuators coupled to the machinery based on the setpoint.