Adaptive nonsingular terminal sliding mode control of MEMS gyroscope based on backstepping design

Fei, Juntao; Yan, Weifeng; Yang, Yuzheng

doi:10.1002/acs.2523

Cited by 31 publications

(32 citation statements)

References 26 publications

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“…In this section, the proposed ABFONTSMC-FNN is applied for trajectory tracking of a z-axis microgyroscope by Matlab/Simulink. Referring to [8] The reference trajectories are well tracked as seen from Figure 4 which demonstrates that the proposed ABFONTSMC-FNN strategy is satisfactory as expected. Figure 5 describes the tracking error of the microgyroscope system along the x-and y-axes.…”

Section: Simulation Studysupporting

confidence: 69%

“…The microgyroscope is composed of a proof mass, sensing mechanisms, and electrostatic actuation which are used to force an oscillatory motion and velocity of the proof mass and to sense the position. Referring to [8], the dynamics of the microgyroscope system can be derived under some assumptions: (1) the stiffness of the spring in the z direction is much larger than that in x and y directions, and the motion of the proof mass is constrained to the x-and y-axes as seen in Figure 1; (2) the gyroscope rotates at a constant angular velocity Ω z over a sufficiently long time interval; and (3) the centrifugal forces can be neglected. Then, the dynamics of the microgyroscope can be expressed in the following form:…”

Section: Dynamics Of the Microgyroscopementioning

confidence: 99%

“…In [7], an adaptive NTSMC was presented using fuzzy wavelet networks to approximate unknown dynamics of robots with an adaptive learning algorithm. Adaptive NTSMC strategy techniques were investigated for the microgyroscope in [8,9].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Backstepping Fuzzy Neural Network Fractional‐Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller

Fei

Liang

2018

Complexity

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An adaptive fractional-order nonsingular terminal sliding mode controller for a microgyroscope is presented with uncertainties and external disturbances using a fuzzy neural network compensator based on a backstepping technique. First, the dynamic of the microgyroscope is transformed into an analogical cascade system to guarantee the application of a backstepping design. Then, a fractional-order nonsingular terminal sliding mode surface is designed which provides an additional degree of freedom, higher precision, and finite convergence without a singularity problem. The proposed control scheme requires no prior knowledge of the unknown dynamics of the microgyroscope system since the fuzzy neural network is utilized to approximate the upper bound of the lumped uncertainties and adaptive algorithms are derived to allow online adjustment of the unknown system parameters. The chattering phenomenon can be reduced simultaneously by the fuzzy neural network compensator. The stability and finite time convergence of the system can be established by the Lyapunov stability theorem. Finally, simulation results verify the effectiveness of the proposed controller and the comparison of root mean square error between different fractional orders and integer order is given to signify the high precision tracking performance of the proposed control scheme.

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Section: Simulation Studysupporting

confidence: 69%

Section: Dynamics Of the Microgyroscopementioning

confidence: 99%

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Adaptive Backstepping Fuzzy Neural Network Fractional‐Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller

Fei

Liang

2018

Complexity

Self Cite

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“…Thanks to their computational efficiency and robustness [4,5], this control method has been applied widely and relevant results can be found in [6][7][8][9]. It works by applying a switching controller to bring the state of the system to a predefined sliding surface in finite time.…”

Section: Introductionmentioning

confidence: 99%

A Novel Reaching Law for Sliding Mode Control of Uncertain Discrete-Time Systems

et al. 2018

Mathematical Problems in Engineering

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This paper proposed a new sliding mode control algorithm for discrete-time systems with matched uncertainty. The new control algorithm is characterized by a new discrete switching surface. Although the exponential reaching law can reduce oscillation, the control effectiveness will be suppressed when the rate of change of disturbance is high. The exponential reaching law cannot force the system states to approach sliding surface ( ) = 0. In order to solve the contradiction between guaranteeing the basic property of quasi-sliding mode and reducing oscillation, a new discrete reaching law is proposed to improve the reaching process of discrete exponent reaching laws. The proposed method not only can force system state to approach the sliding surface ( ) = 0 in less width of the switching manifold than existing studies, but also can alleviate chattering when the system representative points are near zero point. Simulation results are provided to validate the feasibility and reasonability of the method.

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“…The key feature of finite‐time control is that all states in a system are convergent to the equilibrium in finite time . There are 2 excellent properties for systems with finite‐time stability as fast convergence speed around equilibrium point and well disturbance rejection capacity . For high‐order nonlinear systems with mismatched disturbances, backstepping control and other schemes of recursive design are efficient for finite‐time control .…”

Section: Introductionmentioning

confidence: 99%

Adaptive finite‐time control for high‐order nonlinear systems with mismatched disturbances

Yang

Wang

Yang

2017

Adaptive Control & Signal

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In this paper, adaptive finite-time control is addressed for a class of high-order nonlinear systems with mismatched disturbances. An adaptive finite-time controller is designed in which variable gains are adjusted to ensure finite-time stabilization for the closed-loop system. Chattering is reduced by a designed adaptive sliding mode observer which is also used to deal with the mismatched disturbances in finite time. The proposed adaptive finite-time control method avoids calculating derivative repeatedly of traditional backstepping methods and reduces computational burden effectively. Three numerical examples are given to illustrate the effectiveness of the proposed method. KEYWORDS adaptive control, finite-time control, high-order nonlinear systems, mismatched disturbances, sliding mode observers 1 1296

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Adaptive nonsingular terminal sliding mode control of MEMS gyroscope based on backstepping design

Cited by 31 publications

References 26 publications

Adaptive Backstepping Fuzzy Neural Network Fractional‐Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller

Adaptive Backstepping Fuzzy Neural Network Fractional‐Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller

A Novel Reaching Law for Sliding Mode Control of Uncertain Discrete-Time Systems

Adaptive finite‐time control for high‐order nonlinear systems with mismatched disturbances

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