Visible to the public Adaptive observer-based fault diagnosis for sensor in a class of MIMO nonlinear system

TitleAdaptive observer-based fault diagnosis for sensor in a class of MIMO nonlinear system
Publication TypeConference Paper
Year of Publication2017
AuthorsDing, Q., Peng, X., Zhang, X., Hu, X., Zhong, X.
Conference Name2017 36th Chinese Control Conference (CCC)
Date Publishedjul
ISBN Number978-988-15639-3-4
Keywordsadaptive control, adaptive estimation, adaptive observer, adaptive observer structure, convergence of numerical methods, coordinate transformation, diffeomorphic transformation, fault diagnosis, generally multiple-input multiple-output affine systems, global exponential convergence, high-gain observer, Human Behavior, human factor, human factors, Lie derivative, Metrics, MIMO nonlinear system, MIMO systems, multiple fault diagnosis, nonlinear control systems, Observers, pubcrawl, resilience, Resiliency, sensor, sensor parameter fault diagnosis method, Sensors

This paper presents a novel sensor parameter fault diagnosis method for generally multiple-input multiple-output (MIMO) affine nonlinear systems based on adaptive observer. Firstly, the affine nonlinear systems are transformed into the particular systems via diffeomorphic transformation using Lie derivative. Then, based on the techniques of high-gain observer and adaptive estimation, an adaptive observer structure is designed with simple method for jointly estimating the states and the unknown parameters in the output equation of the nonlinear systems. And an algorithm of the fault estimation is derived. The global exponential convergence of the proposed observer is proved succinctly. Also the proposed method can be applied to the fault diagnosis of generally affine nonlinear systems directly by the reversibility of aforementioned coordinate transformation. Finally, a numerical example is presented to illustrate the efficiency of the proposed fault diagnosis scheme.

Citation Keyding_adaptive_2017