Non-linear contour tracking using feedback PID and feedforward position domain cross-coupled iterative learning control

Abstract

In this paper, a position domain cross-coupled iterative learning controller combining proportional–integral–derivative (PID)-type iterative learning control (ILC) and proportional–derivative (PD)-type cross-coupling control (CCC) is presented aiming at non-linear contour tracking in multi-axis motion systems. Traditional individual control methods in the time domain suffer from poor synchronization of relevant motion axes. The complicated computation of coupling gains in CCC and cross-coupled ILC (CCILC) restricts their applications for non-linear contour. The proposed position domain CCILC (PDCCILC) approach introduces a position domain design concept into CCILC to improve synchronization and performance for non-linear contour tracking and it relies less on the accuracy of coupling gains than conventional CCILC. The stability and performance analysis are conducted using a lifted system representation. The contour error vector method is applied to estimate the coupling gains in simulations and experiments. Simulation and experimental results of three typical non-linear contour tracking cases (i.e. semi-circle, parabola and spiral) based on a two-axis micro-motion stage demonstrate superiority and efficacy of the proposed feedback PID and feedforward PDCCILC compared with existing ILC and CCILC in the time domain.

Tracking Control of High Order Input Reference Using Integrals State Feedback and Coefficient Diagram Method Tuning

“…The goal of tracking control is to follow any kind of reference signal. There are some reference signals such as impulse [1] [2], step [3] [4], ramp [5], parabolic [6] [7], parabola [8], periodic [9], sine [10], pulse [1] [11], and random [1], which commonly used in control, robotic and industrial systems as input reference. There are also less popular polynomial references, such as third-order polynomial reference, fourthorder polynomial reference, and higher-order reference (HOR), which are used in the trajectory system or more complex and advanced systems.…”

A LADRC based fuzzy PID approach to contour error control of networked motion control system with time‐varying delays

“…Multi-axis coordinated motion control is an important topics in the field of motion control area, and has applications in a variety of areas, such as the manufacturing and production process like drawing, textile, printing and dyeing, papermaking, rolling steel, semiconductor equipment and engraving machine. It is known that the contour tracking control involves uniaxial position servo control and contour error control, and it has always been a hot research topic since it is one of the main techniques in the multi-axis coordinated motion control [1][2][3][4]. The main goal of position servo control is to improve the position tracking accuracy and the disturbance rejection performance.…”

“…The main goal of position servo control is to improve the position tracking accuracy and the disturbance rejection performance. Many advanced control methods such as PID control with feedforward, sliding mode control, adaptive control and fuzzy control have been presented in [4][5][6][7][8][9]. In the position servo system, the trajectory error is finally reflected in the contour error, and how to reduce the contour error in the position servo system is a very important issue.…”

“…The contour error of the system is reduced by providing additional compensation to each axis without changing the position control loop of each axis. CCC was first proposed by Korea [10], and a variety of improved CCC design methods have been presented one after another, including the PID control, iterative learning control, fuzzy control, et al [4,[11][12][13]. CCC has been recognized as an effective motion control method that can coordinate multi-axis motion and reduce contour errors.…”

Precision Contour Tracking Using Feedback-Feedforward Integrated Control for a 2-Dof Manipulation System

“…In some cases, each motion axis of a multi-input multi-output system is controlled by a separate control loop. A great deal of efforts concerning feedback and feedforward control algorithm, such as PID control [3], robust control [4], iterative learning control [5], predictive control [6] and master-slave control [7], were presented and implemented.…”