DocumentCode
61946
Title
Moment Adaptive Fuzzy Control and Residue Compensation
Author
Tao, Tiantian ; Shun-Feng Su
Author_Institution
Dept. of Comput. & Commun. Eng., Chengshih Univ. of Sci. & Technol., Taipei, Taiwan
Volume
22
Issue
4
fYear
2014
fDate
Aug. 2014
Firstpage
803
Lastpage
816
Abstract
In this paper, a novel control scheme adopted from moment control is proposed. In the proposed approach, an adaptive fuzzy system is employed to learn the effective moment. It is easy to see that such an approach can avoid wild guessing for the effective moment, and as shown in our simulation, can have nice control performance. In traditional adaptive fuzzy control approaches, bounds of system functions are required to facilitate supervisory control so as to have the robust control property. It can be expected that when those bounds used in the supervisory controller are not proper, the output may not be able to follow the reference trajectory satisfactorily. With the proposed moment adaptive fuzzy control, the bound needed is only the supremum of the control variance between two consecutive steps. It is much easier to predict. In our study, in order to further relax this requirement, another adaptive system is employed to estimate the residue of the moment adaptive fuzzy control system. It is called residue compensation in this paper. It can be found that with residue compensation, the approach does not need a supervisory controller, but still can quickly track the reference in a satisfactory fashion. Various simulations are conducted to demonstrate the effectiveness of the proposed approaches.
Keywords
Lyapunov methods; adaptive control; compensation; fuzzy control; robust control; control variance; moment adaptive fuzzy control; residue compensation; robust control property; supervisory control; Adaptation models; Adaptive systems; Equations; Fuzzy control; Mathematical model; Robustness; Supervisory control; Adaptive fuzzy control; Lyapunov stability; cerebellar model articulation controller (CMAC); robust control; supervisory control;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2013.2275168
Filename
6571209
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