Robust coordination control of a pneumatic deburring tool

An efficient robotic deburring method was developed based on an active pneumatic tool. The developed method considers the interaction among the tool, the manipulator, and the workpiece and couples the tool dynamics and a control design that considers deburring process information. The active pneumatic tool was developed based on a single pneumatic actuator, with a passive chamber to provide compliance and reduce chattering caused by air compressibility. A coordination control method was developed for the efficient control of the system, which adopts two-level hierarchical control structure based on a coordination scheme. Robust feedback linearization was utilized to minimize the undesirable effect of the disturbances, such as static and Coulomb frictions and the nonlinear compliance of the pneumatic cylinder stemming from air compressibility. The developed coordination control method demonstrated its efficacy in terms of deburring accuracy and speed. © 2006 Wiley Periodicals, Inc.

[1]  H. Harry Asada,et al.  Design of an adaptable tool guide for grinding robots , 1985 .

[2]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[3]  D. M. Dawson,et al.  Real time adaptive control experiments with a multiple neural network based DCAL controller , 1997, Proceedings of the 1997 IEEE International Conference on Control Applications.

[4]  H.-B. Kuntze,et al.  On the closed-loop control of an elastic industrial robot , 1984 .

[5]  Deepak Shukla,et al.  Multiple neural-network-based adaptive controller using orthonormal activation function neural networks , 1999, IEEE Trans. Neural Networks.

[6]  Takashi Tsubouchi,et al.  Principle of Orthogonalization for Hybrid Control of Robot Manipulators , 1993, Robotics, Mechatronics and Manufacturing Systems.

[7]  Daniel E. Whitney,et al.  Verification of a Dynamic Grinding Model , 1988 .

[8]  Tankut Acarman,et al.  A robust nonlinear controller design for a pneumatic actuator , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[9]  Andreas Jacubasch,et al.  Control algorithms for stiffening an elastic industrial robot , 1985, IEEE J. Robotics Autom..

[10]  John J. Craig,et al.  Hybrid position/force control of manipulators , 1981 .

[11]  H.-B. Kuntze,et al.  A new fuzzy-based supervisory control concept for the demand-responsive optimization of HVAC control systems , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[12]  Yilong Chen Nonlinear feedback and computer control of robot arms , 1984 .

[13]  Mark W. Spong,et al.  Robot dynamics and control , 1989 .

[14]  Neville Hogan,et al.  Impedance control of industrial robots , 1984 .

[15]  Tomonari Furukawa,et al.  Automated polishing of an unknown three-dimensional surface , 1996 .

[16]  Andre Sharon,et al.  Enhancement of Robot Accuracy using Endpoint Feedback and a Macro-Micro Manipulator System , 1984, 1984 American Control Conference.

[17]  J. Descusse,et al.  Decoupling with Dynamic Compensation for Strong Invertible Affine Non Linear Systems , 1985 .

[18]  Danwei Wang,et al.  Robust motion and force control of constrained manipulators by learning , 1995, Autom..

[19]  Y. S. Tarng,et al.  Modeling of the process damping force in chatter vibration , 1995 .

[20]  H. Harry Asada,et al.  Optimal compliance design for grinding robot tool holders , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[21]  Philip Moore,et al.  A practical control strategy for servo-pneumatic actuator systems , 1999 .

[22]  D. E. Whitney,et al.  Historical Perspective and State of the Art in Robot Force Control , 1987 .

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

[24]  Miomir Vukobratovic,et al.  Regulator of minimal variance in hybrid control strategy of manipulation robots , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[25]  Frank L. Lewis,et al.  Robot Control: Dynamics, Motion Planning, and Analysis , 1992 .

[26]  Moshe Cohen,et al.  Learning impedance parameters for robot control using an associative search network , 1991, IEEE Trans. Robotics Autom..

[27]  R. Kelly,et al.  An adaptive impedance/force controller for robot manipulators , 1991 .

[28]  N. Mȧrtensson 14th International Symposium on Industrial Robots, 7th International Conference on Industrial Robot Technology : proceedings : October 2nd-4th, 1984, Gothenburg, Sweden , 1984 .

[29]  Jie Xiao,et al.  Sliding mode control of active suspension for transit buses based on a novel air-spring model , 2003, Proceedings of the 2003 American Control Conference, 2003..

[30]  Ralph L. Hollis A planar XY robotic fine positioning device , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[31]  A. Isidori Nonlinear Control Systems: An Introduction , 1986 .

[32]  Alessandro De Luca,et al.  A sufficient condition for full linearization via dynamic state feedback , 1986, 1986 25th IEEE Conference on Decision and Control.

[33]  G. Duelen,et al.  Automated force control schemes for robotic deburring: Development and experimental evaluation , 1992, Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation.

[34]  Tsuneo Yoshikawa,et al.  Dynamic hybrid position/force control of robot manipulators-controller design and experiment , 1987, IEEE J. Robotics Autom..