Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 46, Issue 7, Pages 1511-1523Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2015.2451116
Keywords
Adaptive robust tracking control; fuzzy approximator; online constructive; surface vehicle
Categories
Funding
- National Natural Science Foundation of China [51009017, 51379002, 51479018]
- Applied Basic Research Funds from the Ministry of Transport of China [2012-329-225-060]
- China Post-Doctoral Science Foundation [2012M520629]
- Program for Liaoning Excellent Talents in University [LJQ2013055]
- Fundamental Research Funds for the Central Universities of China [2009QN025, 2011JC002, 3132013025, 3132014206]
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In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed-and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.
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