naa a22 4500 510823238 CHVBK 20180411083543.0 cr unu---uuuuu 180411e20130301xx s 000 0 eng 10.1007/s12541-013-0055-5 doi (NATIONALLICENCE)springer-10.1007/s12541-013-0055-5 A novel neural second-order sliding mode observer for robust fault diagnosis in robot manipulators [Elektronische Daten] [Mien Van, Hee-Jun Kang, Young-Soo Suh] This paper investigates an algorithm for fault diagnosis in robot manipulators using a novel neural second-order sliding mode observer. Differently from the conventional neural network observer and first-order sliding mode observer for the robust fault estimation schemes, the second-order sliding mode observer is first designed and compared with them. Although the second-order sliding mode observer converges faster and with less error than each of the neural network and the first-order sliding mode observer does, it requires prior knowledge of the upper bound of the fault function. Because of this disadvantage, a neural second-order sliding mode observer is designed, which combines the second-order sliding mode observer with the neural network observer. The resulting observer not only preserves the features of the second-order sliding mode observer but also can improve it by removing the need for prior knowledge of the fault function upper bound. Computer simulation results for a PUMA560 industrial robot are also shown to verify the effectiveness of the proposed strategy. Korean Society for Precision Engineering and Springer-Verlag Berlin Heidelberg, 2013 Fault accommodation nationallicence Fault Detection nationallicence Fault diagnosis nationallicence Nonlinear model nationallicence Neural Network nationallicence Sliding mode observer nationallicence FD : Fault diagnosis nationallicence FDI : Fault detection and isolation nationallicence NN : Neural network nationallicence SM : Sliding mode nationallicence SOSM : Second-order sliding mode nationallicence NSOSM : Neural second-order sliding mode nationallicence EOI : Equivalent Output Injection nationallicence Van Mien Graduate School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut Kang Hee-Jun School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut Suh Young-Soo School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut International Journal of Precision Engineering and Manufacturing Korean Society for Precision Engineering 14/3(2013-03-01), 397-406 2234-7593 14:3<397 2013 14 12541 https://doi.org/10.1007/s12541-013-0055-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12541-013-0055-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Van Mien Graduate School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut NATIONALLICENCE 700 1- Kang Hee-Jun School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut NATIONALLICENCE 700 1- Suh Young-Soo School of Electrical Engineering, University of Ulsan, 680-749, Ulsan, South Korea aut NATIONALLICENCE 773 0- International Journal of Precision Engineering and Manufacturing Korean Society for Precision Engineering 14/3(2013-03-01), 397-406 2234-7593 14:3<397 2013 14 12541 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer