High-Precision Tracking of Piezoelectric Actuator Using Iterative Learning Control and Direct Inverse Compensation of Hysteresis

Jian, Yupei; Huang, Deqing; Liu, Jiabin; Min, Da

doi:10.1109/tie.2018.2826450

Cited by 156 publications

(52 citation statements)

References 37 publications

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“…The ILC has been successfully applied in many practical systems such as the high-precision tracking task of a PEA system 4 and precise control of the laminar flow position. 5 The outstanding tracking performance of ILC comes from its repetition requirements in operation conditions such as identical operation interval and results can be found in other works. [6][7][8][9][10][11][12] However, in many practical applications, the operation terminates early because of system constraints and safety requirements (see related works, [13][14][15][16] where the practical limitations are clearly explained).…”

Section: Introductionmentioning

confidence: 81%

“…The research of ILC has covered various aspects including specific system formulations (eg, discrete‐time and continuous‐time systems), different types of update algorithms (eg, P‐type and PID‐type), and various convergence analysis methods (eg, contraction mapping method and composite energy function method). The ILC has been successfully applied in many practical systems such as the high‐precision tracking task of a PEA system and precise control of the laminar flow position …”

Section: Introductionmentioning

confidence: 99%

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Iterative learning control for noninstantaneous impulsive fractional‐order systems with varying trial lengths

Liu

Wang

Shen

et al. 2018

Intl J Robust & Nonlinear

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Summary In this paper, we propose five iterative learning control (ILC) schemes for noninstantaneous impulsive fractional‐order systems with randomly varying trial lengths. We introduce a domain alignment operator to establish a rigorous convergence analysis for nonlinear fractional‐order systems. This operator guarantees that the input, state, output, and tracking error are constrained in a function space that is designed in advance. Moreover, with the help of this operator, we extend the conventional ILC scheme from discrete systems to continuous and algebraic systems with incorporating redundant tracking information. In addition, nonlinear ILC schemes are also presented with a geometric analysis concept. All proposed schemes are shown to be convergent to the desired tracking trajectory. Two illustrative examples are provided to verify the theoretical results.

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Section: Introductionmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Iterative learning control for noninstantaneous impulsive fractional‐order systems with varying trial lengths

Liu

Wang

Shen

et al. 2018

Intl J Robust & Nonlinear

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“…As a new type of actuator, ultrasonic motor has obvious nonlinear characteristics, and it is not easy to obtain good control performance [1], [2]. In the repeated operation process, based on previous information, iterative learning control (ILC) adopts the iterative method to make the change process of the control quantity gradually approach the expected change process [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

Predictive Iterative Learning Speed Control With On-Line Identification for Ultrasonic Motor

Jingzhuo

Huang

2020

IEEE Access

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Aiming at the needs of ultrasonic motor motion control, a new two-dimensional (2D) predictive control objective function is proposed. Different from the existing methods, the objective function consists of three terms, including the product of the control quantity and the error of the previous control process. Based on the objective function, the predictive iterative learning control (ILC) law is derived by using the design method of generalized predictive control (GPC) without specifying ILC law form in advance. An on-line identification method for model parameters is given to realize effective identification under a small amount of data circumstances, and therefore, the parameters of controller are adjusted adaptively according to the identification results. The proposed control method is validated both in simulation and experiment. The experimental results show that the proposed predictive iterative learning control strategy can obtain better control effect than GPC, and has more obvious characteristics of iterative learning control. It can maintain the expected performance under the condition of intermittent loading and replacing the motor. It presents strong robustness. INDEX TERMS Ultrasonic motor, iterative learning control, generalized predictive control, on-line identification.

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“…H YSTERESIS widely exists in modern electromechanical systems, especially in the systems that contain actuators and sensors made of intelligent materials, such as precision piezoelectric positioning mechanism [1], atomic force microscopy [2], hydraulic piezoelectric valves [3], fast cutting tool servo system [4] and so on. Without hysteresis compensation, it will seriously affect the performance of electromechanical systems, and even cause instability of the systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of a Piezo-Positioning Mechanism With Hysteresis and Input Saturation Using Time Delay Estimation

Li¹,

Zeng²,

Chen³

et al. 2020

IEEE Access

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In this paper, based on backstepping technique and time delay estimation (TDE) technique, an adaptive time delay compensation control scheme is developed for a class of piezoelectric positioning mechanical systems with Bouc-Wen hysteresis and input saturation constraint. The nonlinear part of the Bouc-Wen model is estimated online by TDE, and the TDE error introduced by TDE is compensated online by an adaptive law. Furthermore, an auxiliary variable system is used to deal with the input saturation constraint. Based on the Lyapunov method, the stability of the closed-loop system is analyzed and proved. Two simulation examples are given to demonstrate the effectiveness of the proposed control scheme. INDEX TERMS Hysteresis, time delay control, adaptive control, backstepping.

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High-Precision Tracking of Piezoelectric Actuator Using Iterative Learning Control and Direct Inverse Compensation of Hysteresis

Cited by 156 publications

References 37 publications

Iterative learning control for noninstantaneous impulsive fractional‐order systems with varying trial lengths

Iterative learning control for noninstantaneous impulsive fractional‐order systems with varying trial lengths

Predictive Iterative Learning Speed Control With On-Line Identification for Ultrasonic Motor

Adaptive Control of a Piezo-Positioning Mechanism With Hysteresis and Input Saturation Using Time Delay Estimation

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