Skip to main content
Log in

Implementation of a robust dynamic control for SCARA robot

  • Published:
KSME International Journal Aims and scope Submit manuscript

Abstract

A control system for SCARA robot is designed for implementing a robust dynamic control algorithm. This study focuses on the use of DSPs in the design of joint controllers and interfaces in between the host controller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives, are selected from the commercially available products. The four joint controllers, assigned to each joint separately, are combined into a common system through the mother board hardwarewise and through the global memory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. The global memory stores the common data which can be shared by joint controllers and used by the host computer directly, and it virtually combines the whole system into one. To demonstrate the performance and efficiency of the system, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamic algorithm and a PID compensator. Based upon the derived dynamic equations of SCARA robot, the inverse dynamic algorithm is initially implemented with l msec of control cycle—0.3 msec is actually used for the control algorithm—in this system. The algorithm is found to be inadequate for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore a variable PID algorithm is combined with the inverse dynamic algorithm to reinforce robustness of control. Experimental data using the proposed algorithm are presented and compared with the results obtained from the PID and the inverse dynamic algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

D(q) :

is ann×n inertia matrix

\(C(q, \dot q)\) :

represents the centrifugal and Coriolis terms

G(q) :

is ann×1 gravity vector

\(N(q, \dot q)\) :

is equal to\(C(q, \dot q)\)+G(q)

τ:

is then×1 torque vector

J m :

is an inertia matrix of motor

B m :

is a friction matrix of motor

R :

is a gear ratio matrix

π m :

represents the torque supplied by the actuator

u :

represents a control input vector

K P :

is a proportional gain coefficient

K 1 :

is an integral gain coefficient

D D :

is a differential gain coefficient

K D :

is equal toq d m -q m

η:

is equal to -\([J_m + \overline {D_m } (q_m )]^{ - 1} \varepsilon \)

∈:

is defined by\(\left\| {\ddot e_i } \right\|\) and non diagonal terms ofD m (q m )

\(\overline {D_m } (q_m )\) :

is a diagonal submatrix ofD m (q m )

L :

is the acronym of large

M :

is the acronym of medium

H :

is the acronym of high

μ E (x):

is the input membership function of position error for axes 1, 2, and 4

μ V (y):

is the input membership function of velocity error for axes 1, 2, and 4

μ KD (z):

is the output membership function ofK D for axes 1, 2, and 4

KI (z):

is the output membership function ofK 1 for axes 1, 2, and 4

μ PE (x):

is the input membership function of positive z-directional position error for axis 3

μ PV (y):

is the input membership function of positive z-directional velocity error for axis 3

μ PKD (z):

is the output membership function of positive z-directionalK D for axis 3

μ PKI (z):

is the output membership function of positive z-directionalK 1 for axis 3

μ ME (x):

is the input membership function of negative z-directional position error for axis 3

μ MV (y):

is the input membership function of negative z-directional velocity error for axis 3

μ MKD (z):

is the output membership function of negative z-directionalK D for axis 3

μ MKI (z):

is the output membership function of negative z-directionalK 1 for axis 3

λ i :

represents weights for the input membership functions

References

  • Chen, C. L. and Chang, F. Y., 1996, “Design and Analysis of Neural/Fuzzy Variable Structural PID Control System,”IEE Proc. Control Theory Appl., Vol. 143, No. 2, pp. 200–208.

    Article  MATH  Google Scholar 

  • Digital Signal Processing Products, 1989,Digital Signal Processing Applications with the TMS320 Family, Vol. 1, 2, 3, Texas Instruments Inc.

  • Digital Signal Processing Products, 1993,TMS320C5X User’s Guide, Texas Instruments Inc.

  • Franklin, G. F., Powell, J. D., and Enami-Naeini, A., 1986,Feedback Control of Dynamic System, Addison-Wesley.

  • Kelly, R. and Salgado, R., 1994, “PD Control with Computed Feedforward of Robot Manipulators: A Design Procedure,”IEEE Trans. Robo. and Auto., Vol. 10, No. 4.

  • Lewis, F. L., Abdallak, C. T., and Dawson, D. M., 1993,Control of Robot Manipulators, Macmillan Publishing Company.

  • Lin, K. S., Frantz, G. A., and Simar, R. Jr., 1987, “The TMS320 Family of Digital Signal Processors,”IEEE Proc., Vol. 75, No. 9.

  • Maeno, T., and Kobata, M., 1972, “AC Commulatorless and Brushless Motor,”IEEE Trans. Power Appl. Syst., Vol. PAS-91, pp. 1476–1484.

    Article  Google Scholar 

  • Mamdani, E. H., 1977, “Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Systems,”IEEE Trans. Com., C-26, pp. 1182–1191.

    Article  MATH  Google Scholar 

  • Pillay, P., and Krishnan, R., 1989, “Modeling, Simulation, and Analysis of Permanent-Magnet Motor Drives, Part II: The Brushless DC Motor Drive,”IEEE Trans. Ind. Appl., Vol. 25, No. 2.

  • Rocco, P., 1996, “Stability of PID Control for Industrial Robot Arms,”IEEE Trans. Robo. and Auto., Vol. 12, No. 4.

  • Shyu, K. K., Chu, P. H., and Shang, L. J., 1996, “Control of Rigid Robot Manipulators via Combination of Adaptive Sliding Mode Control and Compensated Inverse Dynamics Approach,”IEE Proc. Control Theory Appl., Vol. 143, No. 3.

  • Song, Y. D., Mitchell, T. L., and Lai, H. Y., 1994, “Control of a Class of Nonlinear Uncertain Systems via Compensated Inverse Dynamics Approach,”IEEE Trans., AC-39, pp. 1866–1871.

    MATH  MathSciNet  Google Scholar 

  • Spong, M. W., and Ortega, R., 1994, “On Adaptive Inverse Dynamics Control of Rigid Robots,”IEEE Trans., AC-39, pp. 1866–1871.

    Google Scholar 

  • Takegaki, M., and Arimoto, S., 1981, “A New Feedback Method for Dynamic Control of Manipulator,”ASME Trans. of Dynamic System, Measurement, and Control, Vol. 103, pp. 119–125.

    Article  MATH  Google Scholar 

  • Zubek, J., Abbondanti, A., and Nordby, C. J., 1975, “Pulsewidth Modulated Inverter Motor Drives with Improved Modulation,”IEEE Trans. Ind. Appl., Vol. 1A-11, pp. 695–703.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, J.M., Lee, MC., Son, K. et al. Implementation of a robust dynamic control for SCARA robot. KSME International Journal 12, 1104–1115 (1998). https://doi.org/10.1007/BF02942584

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02942584

Key Words

Navigation