Iterative Learning Control of Double Servo Valve Controlled Electro Hydraulic Servo System

2011 ◽  
Author(s):  
Yu Shaojuan ◽  
Song Junjun
Keyword(s):  
Iterative Learning Control ◽  
Servo System ◽  
Learning Control ◽  
Iterative Learning ◽  
Servo Valve ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

HYBRID ITERATIVE LEARNING CONTROL FOR POSITION TRACKING OF AN ELECTRO HYDRAULIC SERVO SYSTEM

2019 ◽  
Vol XVI (2) ◽  
pp. 31-42
Author(s):  
Mansoor Zahoor Qadri ◽  
Ahsan Ali ◽  
Inam-ul-Hassan Sheikh
Keyword(s):  
Iterative Learning Control ◽  
Position Control ◽  
Servo System ◽  
Learning Control ◽  
Iterative Learning ◽  
Feed Forward ◽  
Percent Improvement ◽  
Hydraulic Servo ◽  
Hydraulic Servo System ◽  
Feed Forward Controller

Accurate position control of an electro hydraulic servo system (EHSS) is a challenging task due to inherent system nonlinearities, parametric variations and un-modelled dynamics. Since feedback controllers alone cannot provide perfect tracking control, an integration of feedback and feed forward controller is required. A cascaded iterative learning control (ILC) technique for position control of EHSS is proposed in this paper. ILC is a feed forward controller which modifies the reference signal for a feedback fractional order proportional-integral-derivative (PID) controller by learning through current control input and previous error obtained through trails. Unlike other feed forward controllers, ILC works on signal instead of system which eliminates the need of complete knowledge of the system. As compared to other controllers, the proposed technique provides fast convergence without the need of reconfiguring the existing control loop. Simulation and experiments revealed the effectiveness of the proposed technique for EHSS. The obtained results indicated eight percent improvement in rise time and nearly twenty one percent improvement in the settling time.

Suppression of Micro Stick-Slip Vibrations in Hydraulic Servo-System

1998 ◽  
Vol 122 (2) ◽  
pp. 249-256 ◽  
Author(s):  
Toshiyuki Hayase ◽  
Satoru Hayashi ◽  
Kazunori Kojima ◽  
Ikuro Iimura
Keyword(s):  
Feedback Linearization ◽  
Servo System ◽  
Hydraulic Cylinder ◽  
Feedback Gain ◽  
Stick Slip ◽  
Servo Valve ◽  
Wide Range ◽  
Order Of Magnitude ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

This paper deals with suppression of two kinds of micro stick-slip vibrations occurring in a typical computer-controlled hydraulic servo-system. The relevant system consists of a single-rod hydraulic cylinder, an electrohydraulic servo-valve and a personal computer. The discontinuous control signal from a D/A converter causes a stick-slip vibration of micron order of magnitude over a wide range of the feedback gain. Increasing the feedback gain results in the other stick-slip vibration of nearly ten times larger amplitude due to the nonlinear pressure-flow characteristic of the servo-valve. The numerical simulation revealed the latter micro stick-slip vibration could be efficiently suppressed with the feedback linearization technique to compensate the nonlinearity of the servo-valve, while the former one reduced by improving the resolution of the D/A converter. Validities of both the methods were also confirmed with experiment. [S0022-0434(00)00102-7]

An iterative learning control algorithm based on time varying pilot factor

2019 ◽  
Vol 25 (8) ◽  
pp. 1484-1491 ◽  
Author(s):  
Jing Huang ◽  
Zhenxiang Xu ◽  
Guoxiu Li ◽  
Cheng Qiu ◽  
Haitao Huang
Keyword(s):  
Control System ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Sufficient Conditions ◽  
Learning Control ◽  
Critical Issue ◽  
Iterative Learning ◽  
Time Varying ◽  
Initial State ◽  
Hydraulic Servo

Owing to the control system being repetitive and nonlinear, a time-varying pilot factor control algorithm based on iterative learning control is proposed. The convergence of the TPF-ILC control algorithm is mathematically proven and the sufficient conditions are given. Thereafter, the initial state issue of iterative learning is explored, which is the critical issue of iterative learning control. The convergence of the system’s control error and the initial state of every single period have been mathematically proved by using continuous and repetitive properties of the system, even if the initial states of every single iterative learning period are not strictly the same. At the end of this paper, the TPF-ILC algorithm is applied in a hydraulic servo control system, and experimental results indicate the effectiveness and practicability of the TPF-ILC algorithm.

Sign in / Sign up

Export Citation Format

Share Document