Mixed-reality environment for frictional parameters identification in servo-pneumatic system

This paper outlines a method to identify the friction parameters for servo-pneumatic systems using a mixed-reality environment. To acquire system friction parameters accurately can be extremely difficult once the servo-system has been assembled because of its highly nonlinear nature, which causes a great difficulty in servo-pneumatic system modelling and control. In this research, a mixed-reality environment has been employed to determine the friction parameters effectively and efficiently through online identification. Traditionally, friction parameters identification can be performed manually or automatically using traditional optimization methods or modern ones such as neural networks. The advantages of the proposed method are the high accuracy in the estimated parameters, its simplicity and its speed. An experimental case study has been conducted and the results showed the accuracy and effectiveness of the proposed method.

[1]  Q. H. Wu,et al.  Parameter identification for nonlinear pneumatic cylinder actuators , 2003 .

[2]  Demosthenis D. Rizos,et al.  Identification of pre-sliding friction dynamics. , 2004, Chaos.

[3]  Carlos Canudas de Wit,et al.  Adaptive Friction Compensation in Robot Manipulators: Low Velocities , 1991, Int. J. Robotics Res..

[4]  Ashraf Saleem,et al.  Component-based mixed reality environment for the control and design of servo-pneumatic system , 2006 .

[5]  Yildirim Hurmuzlu,et al.  A High Performance Pneumatic Force Actuator System: Part I—Nonlinear Mathematical Model , 2000 .

[6]  Ashraf Saleem,et al.  On-line identification and control of pneumatic servo drives via a mixed-reality environment , 2009 .

[7]  Gary M. Bone,et al.  High steady-state accuracy pneumatic servo positioning system with PVA/PV control and friction compensation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[8]  Carlos Canudas de Wit,et al.  A new model for control of systems with friction , 1995, IEEE Trans. Autom. Control..

[9]  Pud-Tai Mo,et al.  Modelling of servo-controlled pneumatic drives: a generalised approach to pneumatic modelling and applications in servo-drive design , 1989 .

[10]  Bernard Friedland,et al.  On the Modeling and Simulation of Friction , 1990, 1990 American Control Conference.

[11]  P. Moore,et al.  Modelling study and servo-control of air motor systems , 1998 .

[12]  Tegoeh Tjahjowidodo,et al.  Identification of pre-sliding and sliding friction dynamics: Grey box and black-box models , 2007 .

[13]  Carlos Canudas de Wit,et al.  Friction Models and Friction Compensation , 1998, Eur. J. Control.

[14]  Gilda Pour,et al.  Moving toward component-based software development approach , 1998, Proceedings Technology of Object-Oriented Languages. TOOLS 27 (Cat. No.98EX224).

[15]  J. Wang,et al.  Identification of pneumatic cylinder friction parameters using genetic algorithms , 2004, IEEE/ASME Transactions on Mechatronics.

[16]  Philip R. Moore,et al.  Smart components-based servo pneumatic actuation systems , 2000, Microprocess. Microsystems.

[17]  Philip Moore,et al.  Accurate position control of servo pneumatic actuator systems: an application to food packaging , 1999 .

[18]  J. Dieterich.  Modeling of rock friction: 1. Experimental results and constitutive equations , 1979 .