Endpoint Perfect Tracking Control of Robots - A Robust Non Inversion-Based Approach

다국어 초록 (Multilingual Abstract)

This paper presents a simple and robust non inversion-based perfect tracking control (RNIBPTC) strategy for robot manipulators. The proposed approach is capable to eliminate the environmental problems arising from classic feedforward control design and so guarantees an appropriate level of robustness of control system to uncertainties including external disturbances, un-modeled dynamics, friction force and variation of payload. Extensive simulation results performed using a two degree-of-freedom actuated elbow robot prove the effectiveness of the proposed approach. The results are also compared to those obtained from Internal Model Control approach. Using free model of system in control law design is a considerable point in the field of robot manipulator control.

참고문헌 (Reference)

1 D. Yu, "position control of linear servo system using intelligent feedback controller" 128-131, 2006

2 M. F. Mendes, "Variable structure position control of an industrial robotic manipulator" 24 : 2002

3 R.J.Wai, "Tracking control based on neural network strategy for robot manipulator" 51 : 425-445, 2003

4 M. Benosman, "Stable inversion of SISO non minimum phase linear systems through output planning: an experimental application to the one link flexible manipulator" 11 (11): 588-597, 2003

5 G. R. Cho, "Robust trajectory control of robot manipulators using time delay estimation and internal model concept" 3199-3206, 2005

6 Y. Wang, "Robust internal model control with feedforward controller for a high-speed motion platform" 187-192, 2005

7 M. M. Fateh, "Robust control of a high speed manipulator in state space" 1 (1): 38-43, 2008

8 A. Izadbakhsh, "Robust Control methodologies for optical micro electro mechanical system-new approaches and compareson" IEEE-EPEPEMC 2125-2130, 2008

9 M. W. Spong, "Robot Dynamics and Control" John Wiley and Sons 1989

10 L. Qiu, "Performance limitations of non-minimum phase systems in the servo mechanism Problem" 29 (29): 337-349, 1993

11 H. Fujimoto, "Perfect tracking control based on multirate feedforward control with generalized sampling periods" 48 (48): 636-644, 2001

12 A. Isidori, "Output regulation of nonlinear systems" 35 (35): 131-140, 1990

13 A. Piazzi, "Optimal non causal setpoint regulation of scalar systems" 37 : 121-127, 2001

14 A. Piazzi, "Optimal inversion-based control for the set-point regulation of non minimum-phase uncertain scalar systems" 46 : 1654-1659, 2001

15 G. R. Cho, "Neuro-based adaptive internal model control for robot manipulators" 2353-2357, 1995

16 C. S. Chiu, "Mixed feedforward/feedback based adaptive fuzzy Control for a class of MIMO nonlinear systems" 14 (14): 716-727, 2006

17 H. Kwakernaak, "Linear Optimal Control Systems" Wiley-Interscience 1972

18 Q. Li, "Internal model structure in the control of robot manipulators" 6 (6): 571-590, 1996

19 V. Feliu, "Feedforward control of multimode single-link flexible manipulators based on an optimal mechanical design" 54 : 651-666, 2006

20 R.Vilanova, "Feedforward control for uncertain systems, Internal model control approach" 418-425, 2007

21 C. H. An, "Experimental evaluation of feedforward and computed torque control" 5 (5): 368-373, 1989

22 E. J. Adam, "Designing and tuning robust feedforward controllers" Elsevier 28 (28): 1899-1911, 2004

23 J. Y. S. Luh, "An anatomy of industrial robots and their controls" 28 : 133-153, 1983

24 C. G. L. Bianco, "A servo controlsystem design using dynamic inversion" 10 : 847-855, 2002

25 S. Okuma, "A neural network compensator for uncertainties of robotic manipulators" 3303-3307, 1990

26 W. Chen, "A fuzzy compensator for uncertainty of industrial robots" 2001

27 G. F. Franklin, "A foundation of the multivariable information servomechanism problem" Int. Rep, Stanford University 1983