期刊
INFORMATION SCIENCES
卷 181, 期 21, 页码 4895-4907出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2009.06.032
关键词
Cerebellar model articulation controller; Neural compensation; Stability; Overhead crane
资金
- Mexican Government (CONACYT)
- Mexican Government (SNI)
- Mexican Government (SIP-IPN)
- Mexican Government (COFAA-IPN)
- Mexican Government (PIFI-IPN)
In order to control mechanical systems, this paper proposes a novel fast control strategy. The controller includes a normal proportional and derivative (PD) regulator and a fuzzy cerebellar model articulation controller (CMAC). For an overhead crane, this control can realize both position tracking and anti-swing. Using a Lyapunov method and an input-to-state stability technique, the PD control with CMAC compensation is proven to be robustly stable with bounded uncertainties. Real-time experiments are presented comparing this new stable control strategy with regular crane controllers. (C) 2009 Elsevier Inc. All rights reserved.
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