首页> 外文期刊>Journal of low frequency noise, vibration and active control >Design of an Adaptive Fuzzy Sliding Mode Control Using Supervisory Fuzzy Control for Micro-Electro-Mechanical Systems (MEMS) z-axis Gyroscope
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Design of an Adaptive Fuzzy Sliding Mode Control Using Supervisory Fuzzy Control for Micro-Electro-Mechanical Systems (MEMS) z-axis Gyroscope

机译:微机电系统z轴陀螺仪的自适应模糊滑模控制设计

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摘要

This paper presents a novel robust adaptive control strategy for MEMS gyroscope, based on the coupling of the fuzzy logic control with sliding mode control (SMC) approach and adaptive laws. The drawbacks of the conventional SMC include chattering phenomenon and requirement of a priori knowledge of the bounds of uncertainties. In this paper, these problems are suitably attenuated by adopting an adaptive fuzzy sliding mode control (AFSMC) approach which uses two additional fuzzy self-tuning controllers as supervisory fuzzy systems to adaptively tune the output control gain, sliding gain of the AFSMC in order to speed up the convergence rates of the tracking errors and parameter estimations with a desired level of attenuation. Control system stability is proved by Lyapunov method. Numerical simulations using the MEMS gyroscope model with uncertainties demonstrate the effectiveness of this approach in high speed trajectory tracking problems and robustness in estimating the gyroscope parameters and the angular velocity. Numerical simulations show that the chattering is effectively attenuated by this method. Convergence rate of tracking errors and the gyroscope parameters is better than convergence rates in the literature.
机译:本文基于模糊逻辑控制与滑模控制(SMC)方法和自适应律的耦合,提出了一种新颖的鲁棒性MEMS陀螺仪自适应控制策略。常规SMC的缺点包括颤动现象和对不确定性界限的先验知识的要求。在本文中,通过采用自适应模糊滑模控制(AFSMC)方法适当地缓解了这些问题,该方法使用两个附加的模糊自整定控制器作为监督模糊系统来自适应地调整AFSMC的输出控制增益,滑动增益,以便以期望的衰减水平加快跟踪误差和参数估计的收敛速度。控制系统的稳定性通过李雅普诺夫方法证明。使用具有不确定性的MEMS陀螺仪模型进行的数值仿真证明了该方法在高速轨迹跟踪问题中的有效性以及在估计陀螺仪参数和角速度方面的鲁棒性。数值模拟表明,该方法有效地抑制了颤动。跟踪误差和陀螺仪参数的收敛速度优于文献中的收敛速度。

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