Guaranteeing Prescribed Performance Control for Gyrostabilized Platform with Unknown Control Direction Preceded by Hysteresis
Autor: | Jikun Ye, Yexing Wang, Humin Lei, Xiangwei Bu, Yali Xue |
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Rok vydání: | 2019 |
Předmět: |
Lyapunov stability
0209 industrial biotechnology Article Subject Computer science lcsh:Motor vehicles. Aeronautics. Astronautics Aerospace Engineering 02 engineering and technology 01 natural sciences Performance control 020901 industrial engineering & automation Robustness (computer science) Radial basis function neural Control theory Control system Backstepping 0103 physical sciences lcsh:TL1-4050 010301 acoustics |
Zdroj: | International Journal of Aerospace Engineering, Vol 2019 (2019) |
ISSN: | 1687-5974 1687-5966 |
DOI: | 10.1155/2019/2030617 |
Popis: | This paper investigates the problem of precise and quick tracking for gyrostabilized platform (GSP) with unknown hysteresis, unknown control directions, and unknown compound disturbance. Firstly, the dynamic model of GSP is transformed into a strict feedback formulation by designed FD to facilitate the backstepping control system. Secondly, performance functions are constructed at each step of backstepping design to force tracking errors to fall within the prescribed boundaries. Besides, through ingenious transformation, radial basis function neural network (RBFNN) is applied to estimate the unknown control gains preceded by hysteresis. Hence, the problem of prescribed performance control with unknown compound disturbances, unknown hysteresis, and unknown control directions is creatively solved. Furthermore, the exploited controllers are accurate model independent, which guarantees satisfactory robustness of control laws against unknown uncertainties. Finally, the stability of the closed-loop control system is confirmed via Lyapunov stability theory, and numerical simulations are given for a GSP to validate the effectiveness of the proposed controller. |
Databáze: | OpenAIRE |
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