Multi-step prediction error approach for controller performance monitoring

Performance monitoring of model predictive control (MPC) systems has received a great interest from both academia and industry. In recent years some novel approaches for multivariate control performance monitoring have been developed without the requirement of process models or interactor matrices. Among them the prediction error approach has been shown promising, but it is based on single-step prediction and may not be compatible with the MPC objective that is based on multi-step prediction. This paper develops a multi-step prediction error approach for performance monitoring of model predictive control systems, and demonstrates its application in a real industrial MPC performance monitoring and diagnosis problem.