NDLI: Fuzzy supervisory sliding-mode and neural-network control for robotic manipulators

Content Provider	IEEE Xplore Digital Library
Author	Hui Hu Peng-Yung Woo
Copyright Year	1982
Abstract	Highly nonlinear, highly coupled, and time-varying robotic manipulators suffer from structured and unstructured uncertainties. Sliding-mode control (SMC) is effective in overcoming uncertainties and has a fast transient response, while the control effort is discontinuous and creates chattering. The neural network has an inherent ability to learn and approximate a nonlinear function to arbitrary accuracy, which is used in the controllers to model complex processes and compensate for unstructured uncertainties. However, the unavoidable learning procedure degrades its transient performance in the presence of disturbance. A novel approach is presented to overcome their demerits and take advantage of their attractive features of robust and intelligent control. The proposed control scheme combines the SMC and the neural-network control (NNC) with different weights, which are determined by a fuzzy supervisory controller. This novel scheme is named fuzzy supervisory sliding-mode and neural-network control (FSSNC). The convergence and stability of the proposed control system are proved by using Lyapunov's direct method. Simulations for different situations demonstrate its robustness with satisfactory performance.
Sponsorship	IEEE Industrial Electronics Society
Starting Page	929
Ending Page	940
Page Count	12
File Size	496799
File Format	PDF
ISSN	02780046
Volume Number	53
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy control Robot control Sliding mode control Manipulators Uncertainty Couplings Transient response Neural networks Degradation Robust control sliding-mode control (SMC) Fuzzy supervisory control fuzzy supervisory sliding-mode and neural-network control (FSSNC) neural-network control (NNC) robotic control
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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