Current-Cycle Iterative Learning Control for High-Precision Position Tracking of Piezoelectric Actuator System via Active Disturbance Rejection Control for Hysteresis Compensation

Abstract

Yanan (2019) Current-cycle iterative learning control for high-precision position tracking of piezoelectric actuator system via active disturbance rejection control for hysteresis compensation. IEEE Transactions on Industrial Electronics. p. 1.

Modeling and Compensation for Asymmetrical and Dynamic Hysteresis of Piezoelectric Actuators Using a Dynamic Delay Prandtl–Ishlinskii Model

“…In the field of ultra-precision machining, there are higher requirements for the positioning accuracy of micro-position devices such as piezoelectric actuators. Due to the increase in frequency, the dynamic hysteresis characteristics of piezoelectric actuators have a greater impact on the positioning accuracy of the system [ 43 , 44 ].…”

Finite difference based iterative learning control with initial state learning for a class of fractional order two‐dimensional continuous‐discrete linear systems

“…For the finite difference scheme (), borrowed from that in References 20‐22, the following PI‐type ILC law is constructed at the each nodes $$$$ \left\{\begin{array}{c}{x}_{k+1}\left({t}_0,i\right)={x}_k\left({t}_0,i\right)+\Psi {e}_k\left({t}_0,i\right),\\ {}{u}_{k+1}\left({t}_p,i\right)={u}_k\left({t}_p,i\right)+\mathrm{Y}{e}_k\left({t}_p,i\right)+W{\int}_0^{t_p}{e}_k\left(s,i\right) ds,\end{array}\right. $$$$ where $$$$ {e}_k\left({t}_p,i\right)={y}_d\left({t}_p,i\right)-{y}_k\left({t}_p,i\right).$$…”

“…21 The PI (or P)-type ILC law used to achieve the tracking control for fractional order system has been extensively investigated. 22,23 To realize the finite time consensus tracking problem of fractional order multi-agent systems (FOMAS), both P-type and PI-type update laws were applied to generate the control commands for each agent. 24 Furthermore, the PI 𝛽 -type and PD 𝛼 -type ILC law with initial state learning mechanism for FOMAS were introduced.…”

“…In order to tracking the desired discontinuous output trajectory, the P‐type ILC law with initial state learning for impulsive differential equations was explored 21 . The PI (or P)‐type ILC law used to achieve the tracking control for fractional order system has been extensively investigated 22,23 . To realize the finite time consensus tracking problem of fractional order multi‐agent systems (FOMAS), both P‐type and PI‐type update laws were applied to generate the control commands for each agent 24 .…”

Iterative Learning Control for Nonlinear Switched Systems With Constant Time Delay and Noise

“…Trial by trial, the tracking performance of the controlled systems is gradually ameliorated [10], [11]. Because less system knowledge is required for both algorithm designing and convergence insurance, ILC has attracted a great deal of attention and devotion since its first invention several decades ago [12], [13]. Now, it has been one of the most promising control strategies in trajectory tracking fields such as robot [14], chemical batch process [15], traffic control [16], network control [17], and so forth.…”