Real Time Implementation of an Improved Hybrid Fuzzy Sliding Mode Observer Estimator

Real Time Implementation of an Improved Hybrid Fuzzy Sliding Mode Observer Estimator

Volume 2, Issue 1, Page No 214-226, 2017

Author’s Name: Sorin Mihai Radu1, Elena-Roxana Tudoroiu2, Wilhelm Kecs2, Nicolae Ilias1, Nicolae Tudoroiu3,a)

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1Mechanical and Electrical Engineering Faculty, Mechanical Engineering, University of Petrosani, 332006, Romania

2Science Faculty, Mathematics and Informatics, University of Petrosani, 332006, Romania

3John Abbott College, 2127 Lakeshore Road, Sainte-Anne-de-Bellevue, QC, H9X 3L9, Canada

a)Author to whom correspondence should be addressed. E-mail: ntudoroiu@gmail.com

Adv. Sci. Technol. Eng. Syst. J. 2(1), 214-226 (2017); a DOI: 10.25046/aj020126

Keywords: Fuzzy Sliding Mode Observer, Fault Detection and Isolation, Residual Generation, Dc Servomotor Angular Speed

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This paper extends some of our research results disseminated in the most recent awarded international conference paper concerning the implementation in real time of a sliding mode observer state estimator. For the same case study developed in the conference paper, more precisely a DC servomotor angular speed control system, we extend the proposed concept of sliding mode observer state estimator to a fuzzy sliding mode observer version, more suitable in control applications field such as fault detection of the possible faults that might take place inside the actuators and sensors. The hybrid architecture implemented in a real time MATLAB/SIMULINK simulation environment consists of an integrated control loop structure with a switching bench of two sliding mode observers, one built by using a new approach that improves slightly the proposed sliding mode observer for the conference paper, and second one is an improved intelligent fuzzy version sliding mode observer estimator. The both estimators are implemented in SIMULINK to work independently by using a manual switch. The simulation results for the experimental setup show the effectiveness of the improved fuzzy version of sliding mode observer compared to the standard one, as well as its high accuracy and robustness.

Received: 18 December 2016, Accepted: 20 January 2017, Published Online: 28 January 2017

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