Adaptive Backstepping Design of a Microgyroscope

被引:55
作者
Fang, Yunmei [1 ]
Fei, Juntao [1 ]
Yang, Yuzheng [1 ]
机构
[1] Hohai Univ, Coll Elect & Mech Engn, Changzhou 213022, Peoples R China
关键词
adaptive control; backstepping approach; tracking performance; microgyroscope; MEMS TRIAXIAL GYROSCOPE; SLIDING MODE CONTROL;
D O I
10.3390/mi9070338
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
This paper presents a novel algorithm for the design and analysis of an adaptive backstepping controller (ABC) for a microgyroscope. Firstly, Lagrange-Maxwell electromechanical equations are established to derive the dynamic model of a z-axis microgyroscope. Secondly, a nonlinear controller as a backstepping design approach is introduced and deployed in order to drive the trajectory tracking errors to converge to zero with asymptotic stability. Meanwhile, an adaptive estimator is developed and implemented with the backstepping controller to update the value of the parameter estimates in the Lyapunov framework in real-time. In addition, the unknown system parameters including the angular velocity may be estimated online if the persistent excitation (PE) requirement is met. A robust compensator is incorporated in the adaptive backstepping algorithm to suppress the parameter variations and external disturbances. Finally, simulation studies are conducted to prove the validity of the proposed ABC scheme with guaranteed asymptotic stability and excellent tracking performance, as well as consistent parameter estimates in the presence of model uncertainties and disturbances.
引用
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页数:13
相关论文
共 29 条
[1]  
[Anonymous], COMPLEXITY, DOI DOI 10.1109/TCBB.2017.2652453
[2]  
[Anonymous], 1995, NONLINEAR ADAPTIVE C
[3]  
Apostolyuk V., 2006, Theory and Design of Micromechanical Vibratory Gyroscopes
[4]  
Chu Y, 2017, T I MEAS CONTROL
[5]   Backstepping Design of Robust State Feedback Regulators for Linear 2 x 2 Hyperbolic Systems [J].
Deutscher, Joachim .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (10) :5240-5247
[6]   Adaptive backstepping fuzzy sliding mode vibration control of flexible structure [J].
Fang, Yunmei ;
Fei, Juntao ;
Hu, Tongyue .
JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL, 2018, 37 (04) :1079-1096
[7]  
Fang YM, 2014, INT C CONTR AUTOMAT, P361, DOI 10.1109/ICCAS.2014.6988023
[8]   Adaptive fuzzy-neural-network based on RBFNN control for active power filter [J].
Fei, Juntao ;
Wang, Tengteng .
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2019, 10 (05) :1139-1150
[9]   Adaptive fractional order sliding mode controller with neural estimator [J].
Fei, Juntao ;
Lu, Cheng .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2018, 355 (05) :2369-2391
[10]   Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure [J].
Fei, Juntao ;
Lu, Cheng .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (04) :1275-1286