Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 26, Issue 3, Pages 1613-1625Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2017.2737405
Keywords
Adaptive universe-based fuzzy control (AUFC); global model-free control; retractable fuzzy approximator (RFA); uncertain marine vehicle (MV); unmeasurable/unknown trajectory tracking
Funding
- National Natural Science Foundation of China [51009017, 51379002]
- Fund for Dalian Distinguished Young Scholars [2016RJ10]
- Innovation Support Plan for Dalian High-level Talents [2015R065]
- Fundamental Research Funds for the Central Universities [3132016314]
Ask authors/readers for more resources
Motivated by the challenging difficulty in tracking an uncertain marine vehicle (MV) with unknown dynamics and disturbances to any unmeasurable/unknown trajectory, which is unresolved, an adaptive universe-based fuzzy control (AUFC) scheme with retractable fuzzy partitioning (RFP) in global universe of discourse (UoD) is created to achieve global asymptotic model-free trajectory-independent tracking. By defining an error surface and intensively exploring the MV structure, tracking error dynamics are sufficiently trimmed via separating external unknowns including trajectory dynamics and disturbances from internal nonlinearities dependent on tracking errors. An innovative retractable fuzzy approximator (RFA) using the RFP is developed to estimate internal nonlinearities and does not require a priori knowledge on the UoD, thereby contributing to a globally adaptive approximation based control approach in conjunction with Lyapunov synthesis. Together with RFAresiduals, external unknowns are globally dominated by adaptive universal compensators driven by tracking error surface. Eventually, tracking errors and their derivatives globally asymptotically converge to the origin and all other signals of the closed-loop system are bounded. Simulation studies demonstrate superior performance of the proposed AUFC scheme in terms of both tracking and approximation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available