Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Adaptive Control for a Piezoelectric Positioning Platform Based on Improved Recursive Least Squares
by
Li, Yanghao
, Zhang, Shixin
, Li, Hongjun
, Yu, Jun
, Wen, Shengjun
in
Accuracy
/ Adaptive control
/ Compensation
/ Control algorithms
/ Control methods
/ Control systems
/ Controllers
/ Dynamic characteristics
/ Errors
/ Feedback control
/ Feedforward control
/ Hysteresis
/ Industrial applications
/ Least squares
/ Parameter estimation
/ Parameter identification
/ Piezoelectric actuators
/ Proportional integral derivative
/ recursive estimation
/ Smart materials
2025
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Adaptive Control for a Piezoelectric Positioning Platform Based on Improved Recursive Least Squares
by
Li, Yanghao
, Zhang, Shixin
, Li, Hongjun
, Yu, Jun
, Wen, Shengjun
in
Accuracy
/ Adaptive control
/ Compensation
/ Control algorithms
/ Control methods
/ Control systems
/ Controllers
/ Dynamic characteristics
/ Errors
/ Feedback control
/ Feedforward control
/ Hysteresis
/ Industrial applications
/ Least squares
/ Parameter estimation
/ Parameter identification
/ Piezoelectric actuators
/ Proportional integral derivative
/ recursive estimation
/ Smart materials
2025
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Adaptive Control for a Piezoelectric Positioning Platform Based on Improved Recursive Least Squares
by
Li, Yanghao
, Zhang, Shixin
, Li, Hongjun
, Yu, Jun
, Wen, Shengjun
in
Accuracy
/ Adaptive control
/ Compensation
/ Control algorithms
/ Control methods
/ Control systems
/ Controllers
/ Dynamic characteristics
/ Errors
/ Feedback control
/ Feedforward control
/ Hysteresis
/ Industrial applications
/ Least squares
/ Parameter estimation
/ Parameter identification
/ Piezoelectric actuators
/ Proportional integral derivative
/ recursive estimation
/ Smart materials
2025
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Adaptive Control for a Piezoelectric Positioning Platform Based on Improved Recursive Least Squares
Journal Article
Adaptive Control for a Piezoelectric Positioning Platform Based on Improved Recursive Least Squares
2025
Request Book From Autostore
and Choose the Collection Method
Overview
High‐precision positioning is critical in modern industrial applications, yet the inherent hysteresis of piezoelectric actuators limits their accuracy and control performance. To address this problem, this paper proposes an adaptive control method combining feedforward and feedback control. Hammerstein structure is applied to characterize a piezoelectric actuator, which consists of a Prandtl‐Ishlinskii model and a second‐order linear model. The pseudo‐inverse of the Prandtl‐Ishlinskii model is applied as a feedforward controller to compensate for the hysteresis characteristics. As to the feedback control, a recursive least square with adaptive forgetting factor is proposed to estimate system parameters. Based on the estimated parameters, an adaptive self‐tuning controller is designed to track the dynamic characteristics and reduce the feedforward compensation error. Finally, the proposed method is validated on a piezoelectric positioning platform. The results show that the feedforward pseudoinverse can compensate the hysteresis nonlinearity and the compensation error is close to 0. Compared to the PID composite control, the mean absolute error and the root mean square error are reduced by more than 12% and 13%, respectively. This paper proposes an adaptive control method combining feedforward and feedback. The pseudo‐inverse of the Prandtl‐Ishlinskii model is applied as a feedforward controller to compensate for the hysteresis characteristics. As to the feedback close loop, a recursive least square with adaptive forgetting factor (RLS‐AFF) method is proposed to estimate system parameters and then a minimum variance adaptive controller is designed to track the dynamic characteristics.
Publisher
John Wiley & Sons, Inc
Subject
This website uses cookies to ensure you get the best experience on our website.