Piezoelectric Nanopositioning Control Using Second-Order Discrete-Time Terminal Sliding-Mode Strategy

Xu, Qingsong

doi:10.1109/tie.2015.2449772

Cited by 101 publications

(32 citation statements)

References 32 publications

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“…And then, feedback controllers are designed to achieve accurate control. Recently, the commonly used feedback control methods include sliding mode control, neural network control, fuzzy control, or combined control with several controllers [56]- [60]. With the development of computer technology, more and more intelligent control methods will be developed.…”

Section: Precise Motion Platformmentioning

confidence: 99%

A Review of Recent Advances in Robotic Cell Microinjection

Chi

Zhu

2020

IEEE Access

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Cell microinjection is a direct and effective way to transfer external materials into the cell. In the field of modern biomedicine, cell microinjection is very important, no matter in genetics, reproductive health, tumor therapy or others related research directions. Traditional manual cell microinjection has the disadvantages of low efficiency and low survival rate. In contrast, robotic cell microinjection can achieve precise and effective cell microinjection, and can be used in the injection of large quantities of cells. This paper reviews recent advances in robotic cell microinjection technologies. It summarizes the main approaches of key technologies and their advantages and disadvantages, such as cell identification, cell holding, precise positioning platform, cell injection strategy, sensors in cell microinjection, and cell modeling. The conclusion of the investigation is that the robotic cell microinjection has achieved remarkable results and still has great potential for further development. It is expected to be widely used in biomedicine and other fields to realize convenient, fast, and efficient microinjection operations of large number of individual cells. INDEX TERMS Robotic cell microinjection, cell identification, cell holding, precise displacement platform, injection strategy, sensors in cell microinjection, cell modeling.

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Section: Precise Motion Platformmentioning

confidence: 99%

A Review of Recent Advances in Robotic Cell Microinjection

Chi

Zhu

2020

IEEE Access

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“…In the system, the system actual output signal and the desired signal are y(k) and y * (k) . For the nonlinear system (19), consider the following sliding function [22]:…”

Section: B Data-driven Terminal Sliding Mode Control Designmentioning

confidence: 99%

“…The research on the quick response of nonlinear discrete systems is relatively less than that of continuous systems. A novel second-order discrete-time terminal sliding-mode control (2-DTSMC) strategy for a piezoelectric nanopositioning system has developed in [19]. This method was able to achieve quasi sliding mode convergence in time and has high tracking accuracy.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach Based on Terminal Sliding Mode Control for Optimization of Nonlinear Systems

Zhang

Fan

et al. 2020

IEEE Access

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It is difficult for many discrete nonlinear systems to quickly meet control requirements and establish accurate dynamic models. This study presents a control strategy that combines model-free adaptive control and discrete terminal sliding mode control to solve these problems. A novel discrete terminal sliding surface is designed in this strategy. It not only avoids the establishment of system models but also achieves quick response. Firstly, a perturbation observer is established to estimate perturbation of the system and time-varying parameter pseudo-gradient is estimated from input and output data of the system. Secondly, the controller combining the partial form dynamic linearization model free adaptive control and discrete terminal sliding mode control is designed. The stability and convergence of the proposed strategy are proved in theory. Thirdly, the proposed strategy is compared with PID technique and the method of combining model free adaptive control(MFAC) with discrete sliding mode control in chemical system and water tank system respectively. Simulation examples demonstrate that the proposed strategy is superior to others in terms of fast response. This study provides a reference for solving the control problem of discrete nonlinear systems. INDEX TERMS Dynamic models of nonlinear systems, perturbation observer, data-driven control, discrete terminal sliding mode control.

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“…For the second factor, the positioning accuracy can be seriously deteriorated by the inherent hysteresis nonlinearity of PEAs. To deal with the hysteresis nonlinearity of PEAs, there are various control methods in the literature, such as the inversion-based methods [10], [11], the sliding mode control methods [12]- [15], the active disturbance rejection control [16], [17], and some intelligent control methods [18]- [23]. Although these methods are successfully applied in the control of PEAs, to the best of the authors' knowledge, there is no such an attempt of using these advanced control algorithms to deal with the hysteresis nonlinearity in PASSDs.…”

Section: Driving Objectmentioning

confidence: 99%