PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage

Min, Ming; Liang, Wenyu; Feng, Zhao; Ling, Jie; Mamun, Abdullah Al; Xiao, Xiaohui

doi:10.1016/j.mechatronics.2021.102543

Cited by 24 publications

(15 citation statements)

References 31 publications

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“…When the system encounters uncertain disturbances, the feedforward controller cannot adapt in time. Therefore, the feedforward and feedback algorithm are generally combined to form a compound controller [13,14], which can compensate for the hysteresis and eliminate the system disturbance at the same time, as shown in Figure 12. The PID method is simple and practical and is often chosen to be used in the compensation control of the piezoelectric stage [1,2,14].…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…Therefore, the feedforward and feedback algorithm are generally combined to form a compound controller [13,14], which can compensate for the hysteresis and eliminate the system disturbance at the same time, as shown in Figure 12. The PID method is simple and practical and is often chosen to be used in the compensation control of the piezoelectric stage [1,2,14]. The tuning of PID parameters follows the Ziegler-Nichol method and the comprehensive setting method based on the error performance index, especially for the middle part of the hysteresis curve, because the error of this part is relatively large in the whole hysteresis stage.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…When the system encounters uncertain disturbances, the feedforward controller cannot adapt in time. Therefore, the feedforward and feedback algorithm are generally combined to form a compound controller [13,14], which can compensate for the hysteresis and eliminate the system disturbance at the same time, as shown in Figure 12. It can be seen from Figure 11 that the displacement of the compensated piezoelectric stage almost coincides with the expected displacement curve, and the compensated displacement shows a highly linear relationship with the driving voltage.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…To reduce the influence of hysteresis nonlinearity of piezoelectric ceramics and improve the control accuracy, it is usually necessary to establish a model to describe the hysteresis nonlinearity and adopt strategies for compensation control [11]. In a large number of studies, feedforward compensation is a promising scheme [1,[12][13][14]. The piezoelectric hysteresis model is established to track the actual hysteresis curve, and then the feedforward method is chosen to compensate for the hysteresis error.…”

Section: Introductionmentioning

confidence: 99%

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Hysteresis Characteristics and MPI Compensation of Two-Dimensional Piezoelectric Positioning Stage

Wang

Zhang

et al. 2022

Micromachines

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Piezoelectric positioning stage is the core component of precision positioning system and advanced instrument. Its hysteresis characteristics, especially rate-dependent characteristics, are the main factors affecting the positioning or control accuracy. The multi-slope Prandtl–Ishlinskii (MPI) based hysteresis modeling and compensation experiments of two-dimensional piezoelectric positioning stage are discussed. The impact of the driving voltage amplitude and frequency on the hysteresis characteristics of uniaxial piezoelectric actuator in the piezoelectric positioning stage are studied, especially the influence of variable-frequency voltages on the output displacement of a piezoelectric actuator. The MPI compensation control of two-dimensional piezoelectric positioning stage is carried out, and the fitting coefficient R2 is proposed to evaluate the hysteresis compensation accuracy of MPI model. Under the full range driving voltage of 20~120 V, the fitting coefficient reaches more than 99.6%. The experiments of feedforward compensation and feedback compensation are implemented. Having applied the composite triangular-wave signal, the average absolute displacement error of the piezoelectric actuator is 0.1192 μm, as well as the mean square error 0.2949 μm. It demonstrates that the MPI model is effective against hysteresis for two-dimensional piezoelectric positioning stage.

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Section: Experiments and Discussionmentioning

confidence: 99%

Section: Experiments and Discussionmentioning

confidence: 99%

“…When the system encounters uncertain disturbances, the feedforward controller cannot adapt in time. Therefore, the feedforward and feedback algorithm are generally combined to form a compound controller [13,14], which can compensate for the hysteresis and eliminate the system disturbance at the same time, as shown in Figure 12. It can be seen from Figure 11 that the displacement of the compensated piezoelectric stage almost coincides with the expected displacement curve, and the compensated displacement shows a highly linear relationship with the driving voltage.…”

Section: Experiments and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hysteresis Characteristics and MPI Compensation of Two-Dimensional Piezoelectric Positioning Stage

Wang

Zhang

et al. 2022

Micromachines

View full text Add to dashboard Cite

show abstract

“…Therefore, the mounting errors could be reduced by improving the reference tracking accuracy, just for the slave motor on the fly. There are some motion control methods to improve the position accuracy for single motor motion [10][11][12]. Feedback controllers are usually used to implement motion control in order to improve the tracking accuracy, including proportion-integration-differentiation (PID) control, robust control, and sliding mode control (SMC), etc.…”

Section: Introductionmentioning

confidence: 99%

Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control

Feng

et al. 2022

Actuators

Self Cite

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As a core component of the X-ray absorption fine structure spectroscopy (XAFS) system, the multi-channel double-crystal monochromator (DCM) can improve the time resolution of the system significantly. In contrast to the conventional single-channel DCM, the multi-channel DCM includes more pairs of crystals that are located separately in the master and slave motor axis with the same driving direction. However, a mismatched parallelism in the pitch direction, which can result from the manual mounting operation between the two separated crystals, directly affects the performance of the flux and the angular stability of the monochromatic beam. This poses a significant challenge to the precision position tracking of this system. In this paper, the mounting errors were translated into repetitive errors in the slave motor when the master motor was rotated at a constant velocity. Therefore, the iterative learning control (ILC) was considered in order to improve the tracking accuracy of the slave motor motion. The zero-magnitude error controller (ZMETC) was used to calculate the learning function to accelerate the convergence of the control inputs, and the convergence conditions of the control signal and error were also given. To validate the effectiveness of the proposed method, comparative experiments were performed on the motor motion platform. Experimental results indicated that the ILC effectively decreased the parallelism errors of the multi-channel DCM under various trajectories by comparing them with feedback controllers and the ZMETC, respectively.

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Heading control of variable configuration unmanned ground vehicle using PID-type sliding mode control and steering control based on particle swarm optimization

et al. 2022

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PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage

Cited by 24 publications

References 31 publications

Hysteresis Characteristics and MPI Compensation of Two-Dimensional Piezoelectric Positioning Stage

Hysteresis Characteristics and MPI Compensation of Two-Dimensional Piezoelectric Positioning Stage

Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control

Heading control of variable configuration unmanned ground vehicle using PID-type sliding mode control and steering control based on particle swarm optimization

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