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Metamorphic Controller for Collaborative Design of an Optimal Structure of the Control System

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8683))

Abstract

When designing a control system, the customer specifies some control requirements and the expert provides the parameterized optimal controller. A change of the control algorithm to a more advanced one may lead to a better performance of the closed loop system. On the other hand, implementation and parameterization of the advanced controllers require more extensive knowledge. A possible solution is a group of cooperating experts that are able to determine the most suitable control algorithm, depending on the customer’s requirements. However, in practice, hiring more experts is an expensive approach. Hence, the performance of majority of industrial systems is not optimal. The paper presents the metamorphic controller with extended functionality for selection of an optimal control algorithm (including advanced controllers). As a result, only one expert, cooperating with the customer, is sufficient to ensure the optimal system performance. The proposed solution has been implemented and tested on the industrial controller.

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References

  1. Yu, C.C.: Autotuning of PID Controllers: Relay Feedback Approach. Springer, New York (1999)

    Google Scholar 

  2. Li, Y., Ang, K., Chong, G.: PID control system analysis and design. IEEE Control Syst. Mag. 26, 32–41 (2006)

    Google Scholar 

  3. Czeczot, J.: Balance-Based Adaptive Control of a Neutralization Process. Int. J. Control. 79, 1581–1600 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  4. Nocon, W., Metzger, M.: Predictive Control of Decantation in Batch Sedimentation Process. AICHE J. 56, 3279–3283 (2010)

    Article  Google Scholar 

  5. Choinski, D., Metzger, M., Nocon, W.: MAS-Based Cooperative Control for Biotechnological Process-A Case Study. In: Mařík, V., Strasser, T., Zoitl, A. (eds.) HoloMAS 2009. LNCS, vol. 5696, pp. 175–182. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Choinski, D., Metzger, M., Nocon, W.: Cooperative operating control based on virtual resources and user-suited HCI. In: Luo, Y. (ed.) CDVE 2009. LNCS, vol. 5738, pp. 216–223. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  7. Gyoongy, I.J., Clarke, D.W.: On the automatic tuning and adaptation of PID controllers. Control Eng. Pract. 14, 149–163 (2006)

    Article  Google Scholar 

  8. Metzger, M.: Comparison of the RK4M4 RK4LIN and RK4M1 methods for systems with time-delays. Simul. 52, 189–193 (1989)

    Article  MATH  Google Scholar 

  9. Ziegler, J.G., Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME. 64, 759–768 (1942)

    Google Scholar 

  10. Paul, A., Akar, M., Safonov, M.G., Mitra, U.: Adaptive power control for wireless networks using multiple controllers and switching. IEEE Trans. Neural. Netw. 16, 1212–1218 (2005)

    Article  Google Scholar 

  11. Wilson, C., Callen, C.: Close process control translates to quality heat treated parts. Ind. Heating - Pittsburg then Troy. 71, 25–28 (2004)

    Google Scholar 

  12. Li, Y., Ang, K., Chong, G.: Patents, software, and hardware for PID control. IEEE Control Syst. Mag. 26, 42–54 (2006)

    Google Scholar 

  13. Weinzierl, K.: Method for Generating Conrol Parameters From a Response Signal of a Ccontrolled System and System for Adaptive Setting af a PID Controller. U.S. Patent 6,353,766 B1 (2002)

    Google Scholar 

  14. Balasubramanian, S., Brennan, R.W., Norrie, D.H.: An architecture for metamorphic control of holonic manufacturing systems. Comp. Ind. 46, 13–31 (2001)

    Article  Google Scholar 

  15. Brennan, R.W., Zhang, X., Xu, Y., Norrie, D.H.: A Reconfigurable Concurrent Function Block Model and its implementation in Real-Time Java. Integr. Comput.-Aided Eng. 9, 263–279 (2002)

    Google Scholar 

  16. Abdullah, R., Hussain, A., Warwick, K., Zayed, A.: Autonomous Intelligent Cruise Control Using a Novel Multiple-Controller Framework Incorporating Fuzzy-Logic Based Switching and Tuning. Neurocomputing 71, 2727–2741 (2008)

    Article  Google Scholar 

  17. Wang, R., Paul, A., Stefanovic, M., Safonov, M.G.: Cost-detectability and stability of adaptive control systems. In: 44th IEEE Conference on Decision and Control and European Control Conference, Seville, pp. 3584–3589 (2005)

    Google Scholar 

  18. Davendra, D., Zelinka, I., Senkerik, R.: Chaos driven evolutionary algorithms for the task of PID control. Comput. Math. Appl. 60, 1088–1104 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  19. Vyatkin, V.: IEC 61499 Function blocks for embedded and distributed control systems design. ISA, Research Triangle Park (2007)

    Google Scholar 

  20. Stebel, K., Czeczot, J., Laszczyk, P.: General tuning procedure for the nonlinear balance-based adaptive controller. Int. J. Control. 87, 76–89 (2014)

    Article  MathSciNet  Google Scholar 

  21. Skupin, P., Klopot, W., Klopot, T.: Dynamic Matrix Control with partial decoupling. In: 11th WSEAS International Conference on Automation & Information, Iasi, pp. 61–66 (2010)

    Google Scholar 

  22. Klopot, W., Klopot, T., Laszczyk, P., Czeczot, J., Metzger, M.: Practical Implementation of the Nonlinear Control of the Liquid Level in the Tank of Irregular Shape. In: Lee, J., Lee, M.C., Liu, H., Ryu, J.-H. (eds.) ICIRA 2013, Part II. LNCS, vol. 8103, pp. 178–188. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  23. Polakow, G., Metzger, M.: Performance evaluation of the parallel processing producer-distributor-consumer network architecture. Comp. Stand. Inter. 35, 596–604 (2013)

    Article  Google Scholar 

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Klopot, T., Choiński, D., Skupin, P., Szczypka, D. (2014). Metamorphic Controller for Collaborative Design of an Optimal Structure of the Control System. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2014. Lecture Notes in Computer Science, vol 8683. Springer, Cham. https://doi.org/10.1007/978-3-319-10831-5_34

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  • DOI: https://doi.org/10.1007/978-3-319-10831-5_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10830-8

  • Online ISBN: 978-3-319-10831-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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