Tracking of square reference signals using internal model‐based LQG robust controller for positioning of a micro‐electro‐mechanical systems micromirror

Tan, Jiazheng; Sun, Weijie; Yeow, John T. W.

doi:10.1049/mnl.2017.0681

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…; Yi Zhao [10] proposed a multi-loop digital control method to reduce the establishment time and improve the accuracy of the electrostatically driven biaxial micro-mirror. In the simulation and experiment, the positioning performance of the closed-loop control micro-mirror has been significantly improved , achieving an adjustment time of less than 5 ms and a maximum positioning error of less than 5%; Tan [11] proposes an internal-mode-based LQR controller with a Kalman state observer to suppress noise interference, and verifies experimentally that the proposed controller can improve the transient and steady-state response of the MEMS micromirror system with good white noise handling capability; Hessam proposes a robust adaptive neural network-based fuzzy controller [12] for MEMS electrostatic torsion micromirrors, which can improve the tilt performance of the micromirrors and eliminate the "pull-in" phenomenon of the micromirrors. This method is proved by Lyapunov's theory, and the robustness of the system is verified in the presence of input noise.…”

Section: Introductionmentioning

confidence: 99%

Super-twisting Sliding Mode Control Based on Electrostatic MEMS Micromirror Scanning

Lei

Wang

et al. 2023

J. Phys.: Conf. Ser.

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In this paper, a Super-twisting sliding-mode control method based on a nonlinear interference observer is proposed for the external perturbation of MEMS micromirrors during beam scanning. Developing a physical model of electrostatic MEMS micromirror, the Super-twisting sliding-mode control algorithm based on nonlinear interference observer is applied to the electrostatically driven MEMS scanning micromirror with side electrodes, with the demonstration on stability of the control system by Lyapunov theory. The method effectively improves the anti-disturbance performance of the system. The simulation results show that the Super-twisting sliding mode control method based on nonlinear disturbance observer can effectively enhance the disturbance inhibition of the system.

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Section: Introductionmentioning

confidence: 99%

Super-twisting Sliding Mode Control Based on Electrostatic MEMS Micromirror Scanning

Lei

Wang

et al. 2023

J. Phys.: Conf. Ser.

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“…Most closed-loop control tracking strategies with torsional micromirrors are modelbased control methods, e.g., sliding mode control (SMC) [5][6][7], robust control [8][9][10][11], internal model control [7,8], LQG control [12,13], predictive control [14], output regulation control (ORC) [1]. It should be noted that most of the above methods are based on linear or linearized models, which require nonlinear approximation near specific operating points of deflection micromirrors [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Robust control that does not depend on exact model can be used as another option of precise positioning controller design for time-varying systems. Jiazheng T et al has studied the linear feedback composite integral SMC technique and the robust control method of LQG combined with internal mode to improve the transient and steady-state performance of deflected micromirrors, successively [12]. Chen H et al adopted a robust nonlinear control method for the two-dimensional laser scanning micromirror system to achieve accurate positioning and tracking of triangular signals [5,9].…”

Section: Introductionmentioning

confidence: 99%

Online Optimization Method for Nonlinear Model-Predictive Control in Angular Tracking for MEMS Micromirror

Cao

Tan

2022

Micromachines

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In this brief, a precise angular tracking control strategy using nonlinear predictive optimization control (POC) approach is address. In order to deal with the model uncertainty and noise interference, a online Hammerstein-model-based POC is designed using online estimated parameters and model residual. Above all, a rate-dependent Duhem model is used to describe the nonlinear sub-model of the whole Hammerstein architecture for depicting multi-valued mapping nonlinear characteristic. Then, predictive output of angular deflection is obtained by Diophantine function based on linear submodel. Subsequently, the iterative control value depends on estimated parameters through data-driven is acquired. Later, based on the cost function, the iteratively optimization control quantity is fed back to the electromagnetic driven deflection micromirror (EDDM) system on the basis of Hammerstein architecture. It should be stressed that the control value is determined by real-time update model residual and defined cost function. Moreover, the stability of POC strategy is proposed. In addition, experimental result is proposed to validate the effectiveness of the control technique adopted in this paper.

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“…2.0 mm). With the advent of microelectromechanical systems (MEMS) technology [21][22][23][24] , micromachined ultrasound transducers can be constructed with a smaller size. Therefore, such transducers can be promising as medical interventional imaging tools.…”

Section: Introductionmentioning

confidence: 99%

Capacitive micromachined ultrasound transducers for intravascular ultrasound imaging

et al. 2020

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Intravascular ultrasound (IVUS) is a burgeoning imaging technology that provides vital information for the diagnosis of coronary arterial diseases. A significant constituent that enables the IVUS system to attain high-resolution images is the ultrasound transducer, which acts as both a transmitter that sends acoustic waves and a detector that receives the returning signals. Being the most mature form of ultrasound transducer available in the market, piezoelectric transducers have dominated the field of biomedical imaging. However, there are some drawbacks associated with using the traditional piezoelectric ultrasound transducers such as difficulties in the fabrication of high-density arrays, which would aid in the acceleration of the imaging speed and alleviate motion artifact. The advent of microelectromechanical system (MEMS) technology has brought about the development of micromachined ultrasound transducers that would help to address this issue. Apart from the advantage of being able to be fabricated into arrays with lesser complications, the image quality of IVUS can be further enhanced with the easy integration of micromachined ultrasound transducers with complementary metal-oxide-semiconductor (CMOS). This would aid in the mitigation of parasitic capacitance, thereby improving the signal-to-noise. Currently, there are two commonly investigated micromachined ultrasound transducers, piezoelectric micromachined ultrasound transducers (PMUTs) and capacitive micromachined ultrasound transducers (CMUTs). Currently, PMUTs face a significant challenge where the fabricated PMUTs do not function as per their design. Thus, CMUTs with different array configurations have been developed for IVUS. In this paper, the different ultrasound transducers, including conventional-piezoelectric transducers, PMUTs and CMUTs, are reviewed, and a summary of the recent progress of CMUTs for IVUS is presented.

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Tracking of square reference signals using internal model‐based LQG robust controller for positioning of a micro‐electro‐mechanical systems micromirror

Cited by 5 publications

References 24 publications

Super-twisting Sliding Mode Control Based on Electrostatic MEMS Micromirror Scanning

Super-twisting Sliding Mode Control Based on Electrostatic MEMS Micromirror Scanning

Online Optimization Method for Nonlinear Model-Predictive Control in Angular Tracking for MEMS Micromirror

Capacitive micromachined ultrasound transducers for intravascular ultrasound imaging

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