caa a22 4500 606199438 CHVBK 20210128100938.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11045-014-0279-2 doi (NATIONALLICENCE)springer-10.1007/s11045-014-0279-2 Observer based fault detection for two dimensional systems described by Roesser models [Elektronische Daten] [Zhenheng Wang, Helen Shang] Fault detection and isolation for two dimensional (2-D) systems represent a great challenge in both theoretical development and applications. 2-D systems have been commonly represented by the Roesser Model and the Fornasini and Marchesini (F-M) model. Research on fault detection and isolation has been carried out using observer-based methods for the F-M model. In this paper, an observer based fault detection strategy is investigated for systems modelled by the Roesser model. Using the 2-D polynomial matrix technique, a dead-beat observer is developed and the state estimate from the observer is then input to a residual generator to monitor occurrence of faults. An enhanced realization technique is combined to achieve efficient fault detection with reduced computations. Simulation results indicate that the proposed method is effective in detecting faults for systems without disturbances as well as those affected by unknown disturbances. Springer Science+Business Media New York, 2014 Fault detection nationallicence 2-D systems nationallicence Roesser model nationallicence Observer nationallicence State space realization nationallicence Wang Zhenheng School of Engineering, Laurentian University, P3E 2C6, Sudbury, ON, Canada aut Shang Helen School of Engineering, Laurentian University, P3E 2C6, Sudbury, ON, Canada aut Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/3(2015-07-01), 753-775 0923-6082 26:3<753 2015 26 11045 https://doi.org/10.1007/s11045-014-0279-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11045-014-0279-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Zhenheng School of Engineering, Laurentian University, P3E 2C6, Sudbury, ON, Canada aut NATIONALLICENCE 700 1- Shang Helen School of Engineering, Laurentian University, P3E 2C6, Sudbury, ON, Canada aut NATIONALLICENCE 773 0- Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/3(2015-07-01), 753-775 0923-6082 26:3<753 2015 26 11045