Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 50, Issue 7, Pages 2946-2958Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2019.2921733
Keywords
Artificial neural networks; Adaptive systems; Bandwidth; Closed loop systems; Nonlinear dynamical systems; Adaptive control; discrete-time systems; event-triggered (ET) condition; neural networks (NNs); strict-feedback systems
Categories
Funding
- National Natural Science Foundation of China [61773169, 61890922, 61873148, 61873082, U1509205]
- Guangdong Provincial Natural Science Foundation of China [2017A030313381, 2017A030313369]
- Guangzhou Science and Technology Project [201904010295]
- Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing
- Zhejiang Provincial Natural Science Foundation of China [LR16F030003]
- Research Fund for the Taishan Scholar Project of Shandong Province of China
- Fundamental Research Funds for the Central Universities
- Royal Society of the U.K.
- National Post-Doctoral Program for Innovative Talents in China [BX20180202]
- Alexander von Humboldt Foundation of Germany
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This paper proposes a novel event-triggered (ET) adaptive neural control scheme for a class of discrete-time nonlinear systems in a strict-feedback form. In the proposed scheme, the ideal control input is derived in a recursive design process, which relies on system states only and is unrelated to virtual control laws. In this case, the high-order neural networks (NNs) are used to approximate the ideal control input (but not the virtual control laws), and then the corresponding adaptive neural controller is developed under the ET mechanism. A modified NN weight updating law, nonperiodically tuned at triggering instants, is designed to guarantee the uniformly ultimate boundedness (UUB) of NN weight estimates for all sampling times. In virtue of the bounded NN weight estimates and a dead-zone operator, the ET condition together with an adaptive ET threshold coefficient is constructed to guarantee the UUB of the closed-loop networked control system through the Lyapunov stability theory, thereby largely easing the network communication load. The proposed ET condition is easy to implement because of the avoidance of: 1) the use of the intermediate ET conditions in the backstepping procedure; 2) the computation of virtual control laws; and 3) the redundant triggering of events when the system states converge to a desired region. The validity of the presented scheme is demonstrated by simulation results.
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