Global fast non-singular terminal sliding-mode control for high-speed nanopositioning

Wang, Geng; Zhou, Yixuan; Ni, Lei; Aphale, Sumeet S.

doi:10.1016/j.isatra.2022.10.028

Cited by 8 publications

(1 citation statement)

References 57 publications

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“…In this paper, a nonlinear stiffness model for the 4-PPR CPM was established and incorporated into the dynamic model. Based on the dynamic model, an ANFTSMC was proposed, which exhibited the advantage of fast convergence near the equilibrium point compared to traditional SMC [27]. Considering the uncertainties in the parameters of the mechanism, an adaptive law was designed.…”

Section: Introductionmentioning

confidence: 99%

Modeling and control for a long-stroke 4-PPR compliant parallel mechanism

Ren,

Zhang,

Yang

et al. 2024

Int J Intell Robot Appl

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Long-stroke compliant parallel mechanisms(CPMs) are widely used in precision applications. However, stress stiffening and sensitivity to external disturbances in CPMs present challenges in the design of controller. In this paper, the nonlinear stiffness model of the stage is established which is incorporated into the dynamic model . In particular, the method of adaptive nonsingular fast terminal sliding mode control(ANFTSMC) is developed based on the dynamic model. This method addresses the problems of the system parameter uncertainty and the slow convergence of traditional sliding mode control(SMC) at the equilibrium point. The stability of the presented ANFTSMC strategy has been proved based on the Lyapunov analysis. Finally, the proposed control architecture is implemented on the designed 4-prismatic-prismatic-revolute(4-PPR) CPM. The results demonstrate that the developed method exhibits excellent tracking accuracy and robustness compared to the traditional linear sliding mode control(LSMC) and proportional-integral-derivative(PID) control.

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Section: Introductionmentioning

confidence: 99%

Modeling and control for a long-stroke 4-PPR compliant parallel mechanism

Ren,

Zhang,

Yang

et al. 2024

Int J Intell Robot Appl

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Adaptive Fixed‐Time Sliding Mode Control for Trajectory Tracking of Uncertain Dynamical Systems

Yang,

Fan,

et al. 2024

Intl J Robust & Nonlinear

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This paper introduces an innovative adaptive fixed‐time sliding mode control (SMC) method that eliminates chattering, enhancing trajectory tracking accuracy and robustness in nonlinear dynamical systems facing uncertainties and external disturbances. The proposed control scheme ensures fixed‐time convergence of system states to a predefined neighborhood around the origin, independent of initial conditions. An innovative adaptive tuning law is proposed to estimate the unknown upper bounds of synthetic uncertainties and disturbances without requiring prior knowledge. This law forces system states to trend to the sliding surface within a fixed time, achieving stabilization of tracking errors at the origin without undesirable chattering and while avoiding singularities. Comprehensive simulations and comparisons among four control strategies (C1, C2, C3, and C4) demonstrate that the proposed C1 control strategy outperforms others in terms of faster convergence speed, higher tracking accuracy, less chattering, and stronger robustness.

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RBF neural network dynamic sliding mode control based on lambert W function for piezoelectric stick–slip actuator

Li,

Fan,

Zhang

et al. 2024

Review of Scientific Instruments

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This paper presents a novel approach for increasing the precision of high-precision positioning control experiments for a piezoelectric stick–slip actuator system. This is achieved through dynamic sliding mode control with a radial basis function neural network (RBFNN) based on the Lambert W function. The proposed control strategy is divided into two parts: scanning mode control and stepping mode control. For scanning control, a dynamic sliding mode controller was designed to solve the jitter problem in traditional sliding mode control. The introduction of the RBFNN avoids the effects of uncertainty terms and unknown disturbances in the model; reduces the controller gain, which must be adjusted; and improves the robustness of the system to disturbances. The stability of the dynamic sliding mode controller based on the RBFNN was verified through a Lyapunov analysis, and the Lambert W function was introduced to optimize the controller parameters responsible for the time lag in the closed-loop control system. This optimization improved the system’s robustness against time delays, which can adversely affect its performance. Simulation and experimental results indicated that the proposed control strategy achieved a positioning control accuracy of <40 nm during the scanning phase and was robust in the presence of a load. In long-distance positioning control experiments, the control strategy achieved a control target of 40 μm while maintaining the positioning control accuracy and reducing the impact of time lag on the system.

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Global fast non-singular terminal sliding-mode control for high-speed nanopositioning

Cited by 8 publications

References 57 publications

Modeling and control for a long-stroke 4-PPR compliant parallel mechanism

Modeling and control for a long-stroke 4-PPR compliant parallel mechanism

Adaptive Fixed‐Time Sliding Mode Control for Trajectory Tracking of Uncertain Dynamical Systems

RBF neural network dynamic sliding mode control based on lambert W function for piezoelectric stick–slip actuator

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