System and Control Design of a Voice Coil Actuated Mechanically Decoupling Two-Body Vibration Isolation System

Csencsics, Ernst; Thier, Markus; Hainisch, Reinhard; Schitter, Georg

doi:10.1109/tmech.2017.2771440

Cited by 17 publications

(10 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the continuous improvement of measurement and manufacturing accuracy, micro vibration isolation technology has become one of the common core technologies in the field of high-precision manufacturing, processing, and measurement [ 1 , 2 , 3 , 4 ]. In the semiconductor manufacturing field represented by a lithography machine [ 5 ], ultra-precision machining field represented by a diamond lathe [ 6 ], ultra-precision measurement field represented by a super-resolution fluorescence microscope and gravitational wave detection [ 7 , 8 ], a precision vibration isolation system is needed to provide stable and reliable environmental protection.…”

Section: Introductionmentioning

confidence: 99%

Design and Experimentation of a Self-Sensing Actuator for Active Vibration Isolation System with Adjustable Anti-Resonance Frequency Controller

Liu

et al. 2021

Sensors

View full text Add to dashboard Cite

The vibration isolation system is now indispensable to high-precision instruments and equipment, which can provide a low vibration environment to ensure performance. However, the disturbance with variable frequency poses a challenge to the vibration isolation system, resulting in precision reduction of dynamic modeling. This paper presents a velocity self-sensing method and experimental verification of a vibration isolation system. A self-sensing actuator is designed to isolate the vibration with varying frequencies according to the dynamic vibration absorber structure. The mechanical structure of the actuator is illustrated, and the dynamic model is derived. Then a self-sensing method is proposed to adjust the anti-resonance frequency of the system without velocity sensors, which can also reduce the complexity of the system and prevent the disturbance transmitting along the cables. The self-sensing controller is constructed to track the variable frequency of the disturbance. A prototype of the isolation system equipped with velocity sensors is developed for the experiment. The experiment results show that the closed-loop transmissibility is less than −5 dB in the whole frequency rand and is less than −40 dB around, adding anti-resonance frequency which can be adjusted from 0 Hz to initial anti-resonance frequency. The disturbance amplitude of the payload can be suppressed to 10%.

show abstract

Section: Introductionmentioning

confidence: 99%

Design and Experimentation of a Self-Sensing Actuator for Active Vibration Isolation System with Adjustable Anti-Resonance Frequency Controller

Liu

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…For other complex control strategies, such as adaptive control, recursive control, backstepping control, sliding mode control, H-infinity control, model reference control, etc. [1]- [8], the explicit modelbased analysis is also indispensable. It is often supposed that non-linear control is able to achieve better performance than linear control.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Digital Direct Position Servo Control by Neural Network With Implicit Optimal Control Law Learned From Discrete Optimal Position Tracking Data

et al. 2019

View full text Add to dashboard Cite

To get better control performance in motor control, more and more researches tend to apply non-linear control laws in the field of motor control. However, most conventional non-linear control theory is based on explicit model of controlled object and often resulting in complexity. Besides, the control parameters tuning is mainly aiming at stability of the system. No valid direct performance-oriented nonlinear control theory has been proposed. Facing the limitations, this paper presents a direct motor position control in an implicit data-driven manner. Unlike conventional non-linear motor controls that are based on explicit models and with stability-based parameters tuning, this study gives performance-oriented non-linear control by mastering non-linear discrete optimal control law in an implicit data-learning manner. Firstly, optimal data of position tracking problem is obtained by solving optimization problem. Secondly, the implicit discrete optimal control law hidden in data is learned by a BP neural network. Finally, the learned control law is implemented in real-time control to reproduce optimal control performance. Simulation and experiment results validated the feasibility of the data-driven controller, which could be helpful for performance-oriented non-linear control designs. The merits and further improvements are also discussed.INDEX TERMS Position control, implicit discrete optimal control, artificial neural network, motor, data learning.

show abstract

“…The considered amplifiers generate well-controlled output currents that produce torques and forces in different types of electromagnetic actuators such as magnetic bearings or single-/ three-phase permanent magnet motors. Vibration isolation systems, for example, are often used to decouple sensitive positioning stages from ground vibrations caused by nearby equipment or geologic activity [1], [2]. Consequently, their actuators require current signals of extremely low noise in order to prevent the generation of undesired movements.…”

Section: Introductionmentioning

confidence: 99%

“…For the calculation of the load current SNR, the noise of the current signal is considered from DC to 10 kHz, as this frequency range is critical for precision positioning applications: (1) where P (s f F ) is the power of the desired amplifier output signal component s f F with fundamental frequency f F (assuming a sinusoidal signal), and P (s n ) is the power of the noise in a frequency range from DC to 10 kHz, which considers the power of all signal components in this bandwidth, except the power of the fundamental component at s f F and its integer harmonics s kf F , with k ∈ [1, 2, . .…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, a LEM IT 65-S current sensor, in conjunction with a high-precision, low-noise spectrum analyzer, is used to acquire the sinusoidal amplifier output current [15], [24], [25]. This setup is capable of measuring SNR values (according to (1)) in excess of ≈ 108 dB. Amplifier output current fundamental frequencies f F of 35 Hz and 210 Hz are used, which are similar to actuator frequencies in mechatronic positioning systems, and whose harmonics do not interfere with harmonics of the power grid, as described in [15].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Noise Minimization for Ultra-High SNR Class-D Power Amplifiers

Mauerer¹,

Kolar²

2018

CPSS TPEA

View full text Add to dashboard Cite

System and Control Design of a Voice Coil Actuated Mechanically Decoupling Two-Body Vibration Isolation System

Cited by 17 publications

References 23 publications

Design and Experimentation of a Self-Sensing Actuator for Active Vibration Isolation System with Adjustable Anti-Resonance Frequency Controller

Design and Experimentation of a Self-Sensing Actuator for Active Vibration Isolation System with Adjustable Anti-Resonance Frequency Controller

Data-Driven Digital Direct Position Servo Control by Neural Network With Implicit Optimal Control Law Learned From Discrete Optimal Position Tracking Data

Noise Minimization for Ultra-High SNR Class-D Power Amplifiers

Contact Info

Product

Resources

About