Serial-Parallel Estimation Model-Based Sliding Mode Control of MEMS Gyroscopes
| Autor: | Qi Wei, Pengchao Zhang, Rui Zhang, Zhao Wanliang, Ting Yang, Bin Xu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Computer science Vibrating structure gyroscope Gyroscope Sliding mode control Computer Science Applications law.invention Human-Computer Interaction Tracking error Control and Systems Engineering law Control theory Convergence (routing) Radial basis function Electrical and Electronic Engineering Software |
| Zdroj: | IEEE Transactions on Systems, Man, and Cybernetics: Systems. 51:7764-7775 |
| ISSN: | 2168-2232 2168-2216 |
| Popis: | This article proposes a serial-parallel estimation model (SPEM)-based sliding mode control (SMC) of MEMS gyroscope. For the system nonlinearity, the linear-in-parameterized dynamics are formulated and the updating law of the parameter vector is given. For the system uncertainty, the radial basis function (RBF) neural network (NN) is utilized. To improve the approximation accuracy of the compound nonlinearity, the updating laws of the parameter vector and RBF NN weight are constructed by the tracking error and the filtered modeling error derived from SPEM. Furthermore, the fast terminal (FT) SMC is employed to achieve finite-time convergence. The simulation results show that the proposed controller obtains higher tracking accuracy and faster convergence, while the compound nonlinearity approximation is with higher precision. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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