Detection and diagnosis of model-plant mismatch in MIMO systems using plant-model ratio. Issue 1 (2016)

• Record Type: Journal Article
• Authors: Yerramilli, Suraj; Tangirala, Arun K.
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 1(2016)
• Page Start: 266
• Page End: 271
• Publication Date: 2016
• Subjects: model-plant mismatch -- MIMO -- frequency domain -- plant-model ratio -- partial cross-spectral density -- model-based control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.03.064
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The performance of any model-based controller depends on the quality of the model and hence on the model-plant mismatch (MPM). Model maintenance and correction is necessary to achieve desired performance. However, a complete re-identification of the model is usually a costly exercise. Therefore, it would be highly desirable to detect the precise location of the mismatch and update only those parts. The recently introduced plant-model ratio (PMR) was found to be effective in detecting and diagnosing MPM from closed loop operation data for SISO systems. The PMR facilitates a unique identification of the source of mismatch - namely gain, dynamics and delay mismatches. However, direct application of PMR to MIMO systems is a challenge due to the presence of interactions between the various input-output channels. In this paper, the PMR approach is extended to MIMO control systems. It is assumed that the control loop is driven through broadband excitation in the set-points. The key step in the proposed methodology involves decoupling interactions using partial cross-spectral density. The proposed methodology is able to detect the input-output channels with significant mismatch as well as identify the source of mismatch within these channels. The efficacy of this method is demonstrated through two simulation case studies.