Tangent barrier Lyapunov function-based constrained control of flexible manipulator system with actuator failure
Fangyuan Xu
College of Science, Liaoning University of Technology, Jinzhou, China
Search for more papers by this authorCorresponding Author
Li Tang
College of Science, Liaoning University of Technology, Jinzhou, China
Correspondence Li Tang, College of Science, Liaoning University of Technology, Jinzhou, Liaoning 121001, China.
Email: [email protected]
Search for more papers by this authorYan-Jun Liu
College of Science, Liaoning University of Technology, Jinzhou, China
Search for more papers by this authorFangyuan Xu
College of Science, Liaoning University of Technology, Jinzhou, China
Search for more papers by this authorCorresponding Author
Li Tang
College of Science, Liaoning University of Technology, Jinzhou, China
Correspondence Li Tang, College of Science, Liaoning University of Technology, Jinzhou, Liaoning 121001, China.
Email: [email protected]
Search for more papers by this authorYan-Jun Liu
College of Science, Liaoning University of Technology, Jinzhou, China
Search for more papers by this authorFunding information: National Natural Science Foundation of China, 61903168; 61973147; 62025303; Doctoral Research Initiation of Foundation of Liaoning Province, 2020-BS-243; Liaoning Revitalization Talents Program, XLYC2007177; Natural Scientific Research Foundation Guiding Plan of Liaoning Province, 2019-ZD-0701
Abstract
This article puts forward an adaptive neural network fault-tolerant control scheme under the state constraints for the flexible manipulator system with uncertain terms. The dynamic model of the system is described by partial differential equations. The tangent barrier Lyapunov functions are chosen in the design process for the sake of ensuring that all states in the system satisfy the constrained conditions. The uncertainties resulted from load mass, hub inertia, and bending stiffness in the system are approximated by using the universal approximation property of neural networks. The adaptive method is used to counteract the influence of joint motor actuator failure. At the same time, combining with the backstepping design framework to design effective controllers to assure that all signals in the closed-loop system are bounded. Lyapunov stability analysis method is used to prove the stability of the system. Finally, the simulation results prove the availability of the raised control method.
CONFLICT OF INTEREST
All the authors do not have any possible conficts of interest.
Open Research
DATA AVAILABILITY STATEMENT
For data availability, if the researcher needs data of this paper, the corresponding author can provide the simulation data.
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Citing Literature
Special Issue:Emerging Approaches for Nonlinear Parameter Varying (NLPV) Systems
25 November 2021
Pages 8523-8536
