Interval observer-based fault detectability analysis using mixed set-invariance theory and sensitivity analysis approach

ABSTRACT

This paper addresses the characterisation of the minimum detectable fault (MDF) by means of residual sensitivity integrated with the set-invariance theory when using an interval observer-based approach as a fault detection (FD) scheme. Uncertainties (disturbances and noise) are considered as of unknown but bounded nature (i.e. in the set-membership framework). A zonotopic-set representation towards reducing set operations to simple matrix calculations is utilised to bound the state/output estimations provided by the interval observer-based approach. In order to show the connection between sensitivity and set-invariance analyses, mathematical expressions of the MDF are derived when considering different types of faults. Finally, a simulation case study based on a quadruple-tank system is employed to both illustrate and discuss the effectiveness of the proposed approach. The interval observer-based FD scheme is used to test the MDF obtained from the integration of both residual sensitivity analysis and set-invariance theory in the considered case study.

Keywords:

• Fault detection
• bounded uncertainties
• interval observer-based approach
• set-invariance approach
• sensitivity analysis
• zonotopes
• minimum detectable fault

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Masoud Pourasghar http://orcid.org/0000-0002-7010-381X

Additional information

Funding

This work has been partially funded by the Spanish Government Ministerio de Economa y Competitividad (MINECO) through the project DEOCS (ref. DPI2016-76493-C3-3-R), by MINECO and FEDER through the project HARCRICS (ref. DPI2014-58104-R) and by Agència de Gestió d'Ajuts Universitaris i de Recerca.

Notes on contributors

Masoud Pourasghar

Masoud Pourasghar received his B.Sc. degree in Mechanical Engineering from the Azad University of Tehran, Iran, in 2010. He received the M.Sc. degree in Mechanical Engineering from Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia, in 2014. Currently, he is studying automatic control, vision and robotics as a PhD candidate at Universitat Politècnica de Catalunya (UPC). He also works at Institut de Robòtica i Informàtica Industrial (CSIC-UPC). His current research interests include set-theoretic fault diagnosis.

Vicenç Puig

Vicenç Puig received a telecommunications engineering Bsc/Msc degree in 1993 and a PhD degree in automatic control, vision, and robotics in 1999, both from Universitat Politècnica de Catalunya (UPC). He is full professor at the Automatic Control Department and a researcher at Institut deRobòtica i Informàtica Industrial, both at UPC. He is the Director of the Automatic Control Department and the Head of the research group on advanced control systems (SAC) at UPC. He has provided important scientific contributions in the areas of fault diagnosis and fault tolerant control, using interval and linear-parameter-varying models using set based approaches. He has participated in more than 20 European and national research projects in the last decade. He has also led many private contracts with several companies and has published more than 100 journal articles as well as over 350 contributions in international conference/workshop proceedings. He has supervised over 22 PhD dissertations and over 50 Master theses/. He is currently the vice-chair of the IFAC Safe process TC Committee 6.4 (2014–2017). He was the General Chair of the 3rd IEEE Conference on Control and Fault-Tolerant Systems (SysTol 2016) and the IPC Chair of the IFAC Saferprocess 2018.

Carlos Ocampo-Martinez

Carlos Ocampo-Martinez received his electronics engineering degree and his MSc. degree in industrial automation from Universidad Nacional de Colombia, Campus Manizales, in 2001 and 2003, respectively. In 2007, he received his Ph.D. degree in Control Engineering from the Universitat Politècnica de Catalunya (Barcelona, Spain). In 2007-2008, he held a postdoctoral position at the ARC Centre of Complex Dynamic Systems and Control (University of Newcastle, Australia) and, afterwards at the Spanish National Research Council (CSIC), Institut de Robòtica i Informàtica Industrial, CSIC-UPC (Barcelona) as a Juan de la Cierva research fellow between 2008 and 20011. Since 2011, he is with the Universitat Politècnica de Catalunya, Automatic Control Department (ESAII) as Associate Professor in automatic control and model predictive control. From 2014 until 2018, he has been also Deputy Director of the Institut de Robòtica i Informàtica Industrial (CSIC-UPC), a Joint Research Center of UPC and CSIC. His main research interests include constrained model predictive control, large-scale systems management (partitioning and non-centralized control), and industrial applications (mainly related to the key scopes of water and energy).