Virtual CNC system. Part I. System architecture

The paper presents a comprehensive virtual simulation model of a realistic and modular CNC system. The Virtual CNC architecture represents an actual CNC, but with modular feed drives, sensors, motors, and amplifiers. The CNC software library includes a variety of trajectory interpolation and axis control laws. Constant, trapezoidal and cubic acceleration profiles can be selected as a trajectory generation module. The control laws can be selected ranging from a simple PID to complex Pole Placement, Generalized Predictive Control or Sliding Mode Controller with friction compensation. When the Virtual CNC is assembled, its performance can be tested using frequency and time domain response analyses, which are automated. The Virtual CNC includes both analytical tuning methods for linear controllers, as well as Fuzzy Logic based expert auto-tuning system for Adaptive Sliding Mode Control. The paper includes detailed experimental verification of the Virtual CNC.

[1]  A. G. J. Macfarlane,et al.  Knowledge-based control approach for robotic manipulators , 1989 .

[2]  Vinod J. Modi,et al.  Hierarchical Knowledge-based Control of a Deployable Orbiting Manipulator , 2002 .

[3]  Yusuf Altintas,et al.  Sliding Mode Controller Design for High Speed Feed Drives , 2000 .

[4]  Yoram Koren,et al.  Computer control of manufacturing systems , 1983 .

[5]  Carlos Canudas de Wit,et al.  A survey of models, analysis tools and compensation methods for the control of machines with friction , 1994, Autom..

[6]  Yusuf Altintas,et al.  High speed CNC system design. Part I: jerk limited trajectory generation and quintic spline interpolation , 2001 .

[7]  Kaan Erkorkmaz.  Optimal trajectory generation and precision tracking control for multi-axis machines , 2004 .

[8]  Masayoshi Tomizuka,et al.  Zero Phase Error Tracking Algorithm for Digital Control , 1987 .

[9]  Clarence W. de Silva,et al.  An analytical framework for knowledge-based tuning of servo controllers , 1991 .

[10]  Günter Pritschow,et al.  On the Influence of the Velocity Gain Factor on the Path Deviation , 1996 .

[11]  Y. S. Tarng,et al.  A study of backlash on the motion accuracy of CNC lathes , 1996 .

[12]  Clarence W. de Silva,et al.  Intelligent Control: Fuzzy Logic Applications , 1995 .

[13]  Yusuf Altintas,et al.  High speed CNC system design. Part III: high speed tracking and contouring control of feed drives , 2001 .

[14]  F. L. Auspitz.  Systems theory and design , 1988 .

[15]  C. W. de Silva,et al.  Knowledge-based supervisory control system of a fish processing workcell; Part II: Implementation and evaluation , 1998 .

[16]  C. W. de Silva,et al.  Knowledge-based supervisory control system of a fish processing workcell; Part I: system development , 1998 .

[17]  Yusuf Altintas,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2000 .

[18]  Yusuf Altintas,et al.  Open Architecture Modular Tool Kit for Motion and Machining Process Control , 1998 .

[19]  Didier Dumur,et al.  Generalized Predictive Cascade Control (GPCC) for Machine Tools Drives , 1990 .

[20]  Jiri Tlusty,et al.  Effect of low-friction guideways and lead-screw flexibility on dynamics of high-speed machines , 1995 .

[21]  Yusuf Altintas,et al.  High Speed CNC System Design. Part II : Modeling and Identification of Feed Drives , 2001 .

[22]  Karl Johan Åström,et al.  Computer-Controlled Systems: Theory and Design , 1984 .