Skip to main content
Log in

Control System Design Automation for Mechanical Systems

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

In this paper, a user-friendly and comprehensive control system design package called Control System Design Automation (CSDA) is described. The system consists of five main blocks: a requirement interpretation block, a modeling block, an analysis/design block, a database management and knowledge base block, and a verification block. The requirement interpretation block transforms the specifications in terms of the application to those in terms of control. The analysis/design block selects an optimal control structure and determines the controller parameters. In addition to the conventional design methods, CSDA also contains the more recent design methods such as the LMI design approach and the Kessler/Manabe method. The LMI approach can obtain a controller which satisfies multiple specification items at the same time. The configuration of the system as well as the analysis/design block are described in detail in this paper.

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

References

  1. Reilly, J., Levine, W. S, Eadan, E., and Huang, C.: A computer-aided optimization-based controller design tool, in: Proc. Am. Control Conf., 1991, pp. 990–995.

  2. Murakami, K., Knnno, T., Kurotani, K., and Takano, M.: Optimization system for control system design, IEEE Tokyo Section Denshi Tokyo 33 (1994), 124–127.

    Google Scholar 

  3. Gahinet, P., Nemirowski, A., Laub, A. J., and Chilali, M.: LMI Control Toolbox, The Math Works Inc., 1994.

  4. Hori, Y.: Novel methods and recent trends of 2-inertia resonant system control, in: ROBOMEC '94, 1994 (in Japanese), pp. 1278–1283.

  5. Boyd, S. et al.: Linear Matrix Inequalities in System and Control Theory, SIAM, 1994.

  6. Chilali, M. and Gahinet, P.: H-∞ design with pole placement constraints: an LMI approach, Trans. Automatic Control 41(3) (1996), 358–367.

    Google Scholar 

  7. Sugie, T. and Hamamoto, K.: Controller design of two mass-spring system via LMI, Systems Control and Information 9(5) (1996), 219–226 (in Japanese).

    Google Scholar 

  8. Taylor, J. H.: Database management for computer-aided control engr., in: M. Jamshidi and C. J. Herget (eds), Recent Advances in Computer-Aided Control Systems Engineering, Elsevier Science, 1992, pp. 127–150.

  9. Pang, G. K. H.: MEDAL: Matrix & expert system development aid language, in: Proc. IEEE Symp. on Computer-Aided Control System Design, Napa, California, USA, 1992, pp. 148–155.

    Google Scholar 

  10. Pang, G. K. H.: Knowledge-based control system design, in: M. Jamshidi and C. J. Herget (eds), Recent Advances in Computer-Aided Control Systems Engineering, Elsevier Science, 1992, pp. 127–150.

  11. Pang, G. K. H.: A knowledge environment for an interactive control system design package, Automatica 28(3) (1992), 473–491.

    Google Scholar 

  12. Lipatov, A. V. and Sokolov, N. I.: Some sufficient conditions for stability and instability of continuous linear stationary systems, Automat. Remote Control 39 (1979), 1285–1291 (translated from Automatika i Telemekhanika 9 (1978), 30–37).

    Google Scholar 

  13. Ng, W. Y.: Perspectives on search-based computer-aided control system design, Control System Magazine 13(2) (1993), 65–72.

    Google Scholar 

  14. Boyd, S. P. and Barratt, C. H.: Linear Controller Design: Limits of Performance, Prentice-Hall, 1991.

  15. Kessler, C.: Article on theory of multiple loop control (translated from Ein Beitrag zur Theorie mehrschleifiger Regelungen), Regelungstechnik 8(8) (1960), 261–266.

    Google Scholar 

  16. Manabe, S.: Coefficient diagram method as applied to the attitude control of controlled biasmomentum satellite, in: Proc. 13th IFAC Symposium on Automatic Control in Aerospace, Palo Alto, California, Sept. 12–16, 1994, pp. 322–327.

  17. Blaschke, F.: Das Verfahren der Feldorientierung zur Regelung der Drehfeldmaschine, Dr.-Ing. Dissertation, Technische Universitä Braunschweig, 1974.

  18. Hori, Y.: Two-mass system control based on resonance ratio control and Manabe polynomials, in: Proc. First Asian Control Conf., Vol. 3, 1994, pp. 741–744.

    Google Scholar 

  19. Voda, A. A. and Landau, I. D.: A method for the auto-calibration of PID controllers,Automatica 31(1) (1995), 41–53.

    Google Scholar 

  20. Manabe, S.: Coefficient diagram method: a polynomial design approach, to be submitted to Journal of Guidance, Control, and Dynamics.

  21. Herbert, H.: Automotive control: from concept to experiment to product, in: Proc 9th IEEE Int. Symp. on Computer-Aided Control System Design, 1996, pp. 129–134.

  22. Taylor, J. H. and Seres, P.: An intelligent front end for control system implementation, in: Proc 9th IEEE Int. Symp. on Computer-Aided Control System Design, 1996, pp. 7–13.

  23. Whidborne, J. F., Postlethwaite I., and Gu, D.-W.: A mixed optimization approach to multiobjective computer-aided control system design, in: Proc 9th IEEE Int. Symp. on Computer-Aided Control System Design, 1996, pp. 309–314.

  24. Sienel, W., Bunte, T., and Ackermann, J.: PARADISE – Parametric robust analysis and design interactive software environment: A Matlab-based robust control toolbox, in: Proc 9th IEEE Int. Symp. on Computer-Aided Control System Design, 1996, pp. 380–385.

  25. Chipperfield, A. J. and Fleming, P. J.: PARSIM: A paralel optimization tool, IEEE Control Systems 15(2) (1995), 48–53.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Maekawa, K., Pang, G.K.H. Control System Design Automation for Mechanical Systems. Journal of Intelligent and Robotic Systems 21, 239–256 (1998). https://doi.org/10.1023/A:1007903219173

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1007903219173

Navigation