| Autor: |
Dong, Jiayu, Zhao, Meijiao, Zhao, Li, Cheng, Min |
| Předmět: |
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| Zdroj: |
Transactions of the Institute of Measurement & Control; Feb2023, Vol. 45 Issue 4, p637-648, 12p |
| Abstrakt: |
In this paper, a novel finite-time fault-tolerant trajectory tracking controller is created to render a marine vehicle to enhance tracking performance in the presence of complex unknown variables, including model uncertainties, environmental disturbances, and actuator faults. An adaptive fault-tolerant finite-time sliding mode controller is designed by introducing adaptive control techniques, the non-singular fast terminal sliding mode (NSFTSM) function, and a radial base function (RBF) neural network. The radial base function neural network (RBFNN) is developed to eliminate the influences of model uncertainties and environmental disturbances. A fault compensation by integrating the adaption technique is designed to reduce the effects of actuator faults and approximation errors. Suffering from uncertainties and actuator faults, the proposed finite-time tracking controller can track the desired trajectory with high precision. Simulation results and compared simulations indicate the efficiency and superiority of the proposed controller. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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