Performance diagnosis of model predictive controller based on eigenvector subspace distance

Key words:  predictive control  performance diagnosis  performance assessment  distance clustering

Abstract:

Aiming at the shortcoming that current research on controller performance assessment can 't isolate the root causes for the poor performance,a novel method of model predictive controller performance diagnosis based on distance clustering was proposed. The concept of eigenvector subspace which can describe the characteristic of various subspace was presented, classification could be made by calculating the distances between the current subspace and the predefined ones, and then it can correctly locate the causes contributed to the performance variation. The simulation results on the Wood Berry validate the efficiency of the novel method.