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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Jianjuen Hu Pratt, G. | 
| Copyright Year | 1999 | 
| Description | Author affiliation: Leg Lab., MIT, Cambridge, MA, USA (Jianjuen Hu) | 
| Abstract | A self-organizing CMAC neural network mechanism and an CMAC based adaptive control scheme are presented. Two main efforts have been made in this study. One is on the self-organizing mechanism of CMAC neural network. The CMAC basis functions with a stair-waveform are introduced. A data clustering technique is used in reducing the memory size significantly and a structural adaptation technique is developed in order to accommodate new data sets. Another effort is on the unsupervised learning scheme, which is based on a Lyapunov index function. Adaptive dynamic control is implemented by means of the self-organizing CMAC neural network, and it can identify the unmodelled dynamics of a plant and ensures asymptotic system stability in a Lyapunov sense. The adaptive control system has been applied in the locomotion control of a bipedal walking robot successfully in simulation. | 
| Starting Page | 259 | 
| Ending Page | 265 | 
| File Size | 618282 | 
| Page Count | 7 | 
| File Format | |
| ISBN | 0780356659 | 
| ISSN | 21589860 | 
| DOI | 10.1109/ISIC.1999.796665 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 1999-09-17 | 
| Publisher Place | USA | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Neural networks Adaptive systems Programmable control Adaptive control Brain modeling Legged locomotion Motor drives Robot kinematics Biological system modeling Robot sensing systems | 
| Content Type | Text | 
| Resource Type | Article | 
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