Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 23, Issue 4, Pages 1228-1241Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2014.2348017
Keywords
Adaptive output-feedback tracking control; fuzzy logic systems (FLS); multi-input multi-output (MIMO) stochastic nonlinear systems; unknown control directions; unknown dead-zones
Funding
- National Natural Science Foundation of China [61203008, 61374113, 61074014, 51179019]
- Program for Liaoning Innovative Research Team in University [LT2012013]
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In this paper, an adaptive fuzzy backstepping output-feedback tracking control approach is proposed for a class of multi-input and multi-output (MIMO) stochastic nonlinear systems. The MIMO stochastic nonlinear systems under study are assumed to possess unstructured uncertainties, unknown dead-zones, and unknown control directions. By using a linear state transformation, the unknown control coefficients and the unknown slopes characteristic of the dead-zones are lumped together, and the original system is transformed to a new system on which the control design becomes feasible. Fuzzy logic systems are used to approximate the unstructured uncertainties, and a fuzzy state observer is designed to estimate the unmeasured states. By introducing a special Nussbaum gain function into the backstepping control design, a stable adaptive fuzzy output-feedback tracking control scheme is developed. The main features of the proposed adaptive control approach are that it can guarantee the stability of the closed-loop system, and the tracking errors converge to a small neighborhood of zero. Moreover, it can solve the problems of unknown control direction, unknown dead-zone, and unmeasured states simultaneously. Two simulation examples are provided to show the effectiveness of the proposed approach.
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