BAYESIAN APPROACH FOR CONSTRAINT ANALYSIS OF MPC AND INDUSTRIAL APPLICATION

Profit margins from plant operations may be improved by changing the constraints so as to increase the degrees of freedom for control. Due to the presence of disturbances the chances of operating the plant outside the set limits cannot be ruled out. Thus, the expected return should be estimated by taking into account the variability. Bayesian Statistics can be used to estimate these probabilities subject to changes in operating constraint limits. The maximum a posteriori estimate of the process state due to the change in the operating conditions can be inferred using Bayesian methods and the profits or return thus obtained can be estimated. Also the decisions to obtain target value of the return can be made using the Bayesian methods.