Piezo Actuator Hybrid Modeling for Nonlinear Inverse Control in Diamond Turning

1999 ◽  
Author(s):  
Dongwoo Song ◽  
C. James Li
Keyword(s):  
Pid Control ◽  
Inverse Dynamics ◽  
Feedforward Control ◽  
Diamond Turning ◽  
Piezo Actuator ◽  
Positioning System ◽  
Preisach Model ◽  
Hysteresis Model ◽  
Inverse Control ◽  
Spring Mechanism

Abstract This paper describes a micro-positioning system based on piezo actuators and a spring mechanism, and a hybrid hysteresis model integrating a neural network and Preisach model to identify the inverse dynamics of the micro-positioning system. To improve the workpiece form accuracy in diamond turning, feedforward control using the hybrid inverse model and feedback PID control were applied individually and in combination. The performance of these controllers are compared in actual cutting tests.

Tracking control of a 3-dimensional piezo-driven micro-positioning system using a dynamic Prandtl–Ishlinskii model

2021 ◽  
pp. 1045389X2110482
Author(s):  
Wei Zhu ◽  
Feifei Liu ◽  
Fufeng Yang ◽  
Xiaoting Rui
Keyword(s):  
Power Amplifier ◽  
Dynamic Characteristics ◽  
Tracking Control ◽  
Feedforward Control ◽  
Positioning System ◽  
Hysteresis Model ◽  
Tracking Accuracy ◽  
Simple Method ◽  
3 Dimensional ◽  
Rate Dependent

A controller composed of a feed-forward loop based on a novel dynamic Prandtl–Ishlinskii (P-I) model and a PID feedback control loop is developed to support a 3-dimensional piezo-driven micro-positioning system for high-bandwidth tracking control. By considering the dynamic characteristics of the power amplifier, the dynamic P-I model can accurately describe the rate-dependent hysteresis of piezoelectric stack actuators (PSAs). To ensure that the hysteresis model is independent of system load, the P-I hysteresis operator in that model characterizes the relationship between the output force and the input voltage of PSAs. The dynamics equation of the mechanical is established by using the cutoff modal method. The feedforward control is designed based on the dynamic hysteresis model to reduce the rate-dependent hysteresis. The PID control is incorporated with the feedforward control to increase the tracking accuracy. Experimental results indicate that the controller can overcome the hysteresis efficiently and preserve good positioning accuracy in 1–100 Hz bandwidth. Just by introducing the dynamic characteristics of the power amplifier, which can be expressed as a first-order differential equation, the P-I model can accurately describe the rate-dependent hysteresis of the PSA, which provides a simple method to describe and control piezoelectric actuators and piezo-driven systems in a wide frequency.

Nonlinear Piezo-Actuator Control by Learning Self-Tuning Regulator

1993 ◽  
Vol 115 (4) ◽  
pp. 720-723 ◽  
Author(s):  
C. James Li ◽  
Homayoon S. M. Beigi ◽  
Shengyi Li ◽  
Jiancheng Liang
Keyword(s):  
Parameter Estimation ◽  
Tracking Error ◽  
Diamond Turning ◽  
Piezo Actuator ◽  
Positioning System ◽  
Tool Positioning ◽  
Repetitive Tasks ◽  
Self Tuning ◽  
Learning Parameter ◽  
Actuator Control

This paper presents a learning self-tuning (LSTR) regulator which improves the tracking performance of itself while performing repetitive tasks. The controller is a self-tuning regulator based on learning parameter estimation. Experimentally, the controller was used to control the movement of a nonlinear piezoelectric actuator which is a part of the tool positioning system for a diamond turning lathe. Experimental results show that the controller is able to reduce the tracking error through the repetition of the task.

scholarly journals Fuzzy PID Feedback Control of Piezoelectric Actuator with Feedforward Compensation

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Ziqiang Chi ◽  
Minping Jia ◽  
Qingsong Xu
Keyword(s):  
Feedback Control ◽  
Piezoelectric Actuator ◽  
Pid Control ◽  
Feedforward Control ◽  
Comparative Investigation ◽  
Preisach Model ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Scheme ◽  
Feedforward Controller

Piezoelectric actuator is widely used in the field of micro/nanopositioning. However, piezoelectric hysteresis introduces nonlinearity to the system, which is the major obstacle to achieve a precise positioning. In this paper, the Preisach model is employed to describe the hysteresis characteristic of piezoelectric actuator and an inverse Preisach model is developed to construct a feedforward controller. Considering that the analytical expression of inverse Preisach model is difficult to derive and not suitable for practical application, a digital inverse model is established based on the input and output data of a piezoelectric actuator. Moreover, to mitigate the compensation error of the feedforward control, a feedback control scheme is implemented using different types of control algorithms in terms of PID control, fuzzy control, and fuzzy PID control. Extensive simulation studies are carried out using the three kinds of control systems. Comparative investigation reveals that the fuzzy PID control system with feedforward compensation is capable of providing quicker response and better control accuracy than the other two ones. It provides a promising way of precision control for piezoelectric actuator.

Trajectory Tracking of Underactuated Multibody Systems

2011 ◽  
Author(s):  
Stefan Reichl ◽  
Wolfgang Steiner
Keyword(s):  
Trajectory Tracking ◽  
Multibody Systems ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Feedforward Control ◽  
Equations Of Motion ◽  
Three Dimensional ◽  
Differential Algebraic Equations ◽  
State Variables ◽  
Algebraic Equations

This work presents three different approaches in inverse dynamics for the solution of trajectory tracking problems in underactuated multibody systems. Such systems are characterized by less control inputs than degrees of freedom. The first approach uses an extension of the equations of motion by geometric and control constraints. This results in index-five differential-algebraic equations. A projection method is used to reduce the systems index and the resulting equations are solved numerically. The second method is a flatness-based feedforward control design. Input and state variables can be parameterized by the flat outputs and their time derivatives up to a certain order. The third approach uses an optimal control algorithm which is based on the minimization of a cost functional including system outputs and desired trajectory. It has to be distinguished between direct and indirect methods. These specific methods are applied to an underactuated planar crane and a three-dimensional rotary crane.

Linear Motor Control Algorithm and Experimental Research Based on Feedforward Fuzzy PID

2014 ◽  
Vol 620 ◽  
pp. 363-368
Author(s):  
Lian Xia ◽  
Jing Qiu ◽  
Jiang Han
Keyword(s):  
Pid Control ◽  
Feedforward Control ◽  
Tracking Error ◽  
Response Speed ◽  
Linear Motor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Theory Analysis ◽  
Speed Tracking ◽  
Load Change

In this paper, theory analysis, the MATLAB research and experimental verification about feedforward fuzzy PID control have been performed by combining the characteristics of the PID, feedforward control and fuzzy control. Simulation results show that the feedforward fuzzy PID control could improve the response speed of the system and reduce the tracking error of the system which shows the obvious superiority compared with the PID, feedforward PID, and fuzzy PID. Load experiment for such four kinds of control modes is done on the linear motor platform, and the experimental results show that the accuracy of the feedforward fuzzy PID control is obviously higher than the other three kinds of control modes and the feedforward fuzzy PID control is easier to be implemented. The position error of feedforward fuzzy PID control is changeless during the load change, and the change of the speed tracking error is small, which proves that the feedforward fuzzy PID control is suitable for the condition of load change or the great disturbance.

A SIMPLE DYNAMIC PREISACH HYSTERESIS MODEL FOR FeSi MATERIALS

2003 ◽  
Vol 17 (11) ◽  
pp. 2325-2331
Author(s):  
M. LU ◽  
P. J. LEONARD ◽  
P. MARKETOS ◽  
T. MEYDAN ◽  
A. J. MOSES
Keyword(s):  
Applied Field ◽  
Hysteresis Loops ◽  
Cosine Function ◽  
Preisach Model ◽  
Common Phenomenon ◽  
Hysteresis Model ◽  
Dynamic Hysteresis ◽  
Model Based ◽  
Hysteresis Operator ◽  
Preisach Hysteresis

Dynamic hysteresis property is a common phenomenon in FeSi materials under time-varied applied field. This paper presented a dynamic hysteresis model based on Preisach scheme. The rectangular-shaped elementary hysteresis operator with two states in classical Preisach model is replaced by a non-rectangular shaped one with multiple states. The output of each state is calculated by a cosine function. The proposed dynamic hysteresis model is experimently tested by comparing the simulated hysteresis loops to experimental ones. The model can be used to describe the dynamic hysteresis in FeSi material for magnetizing frequencies from quasi-static to several hundred Hertz.

Model-based PID control of a Dielectric Electro-Active Polymer Positioning System

2014 ◽  
Vol 47 (3) ◽  
pp. 10926-10933 ◽  
Author(s):  
G. Rizzello ◽  
D. Naso ◽  
A. York ◽  
S. Seelecke
Keyword(s):  
Pid Control ◽  
Positioning System ◽  
Model Based
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