|
Vol: 52(66) No: 1 / March 2007 On Iterative Approaches for Optimal Tuning of Two-Degree-of-Freedom Controllers Radu-Emil Precup Department of Automation and Applied Informatics, "Politehnica" University of Timisoara, Faculty of Automation and Computers, Bd. Vasile Parvan 2, RO-300233, Timisoara, Romania, phone: +40-256-4032-26, e-mail: radu.precup@aut.upt.ro, web: http://www.aut.upt.ro/~rprecup Stefan Preitl Department of Automation and Applied Informatics, "Politehnica" University of Timisoara, Faculty of Automation and Computers, Bd. Vasile Parvan 2, RO-300233, Timisoara, Romania, phone: +40-256-4032-29, e-mail: stefan.preitl@aut.upt.ro Keywords: iterative feedback tuning, iterative learning control, optimization, digital simulation. Abstract The paper presents aspects concerning the Iterative Feedback Tuning (IFT) approach and the Iterative Learning Control (ILC) approach used in the optimal tuning two-degree-of-freedom (2-DOF) controllers. There are presented both theoretical aspects concerning the IFT and the ILC and their implementation. Theoretical results are validated considering a case study dedicated to a second-order non-oscillatory plant controlled by a 2-DOF PID controller. References [1] H. Hjalmarsson, S. Gunnarsson and M. Gevers, “A convergent iterative restricted complexity control design scheme”, Proceedings of the 33rrd IEEE Conference on Decision and Control, Lake Buena Vista, FL, pp. 1735 – 1740, 1994. [2] H. Hjalmarsson, M. Gevers, S. Gunnarsson and O. Lequin, “Iterative Feedback Tuning: theory and applications”, IEEE Control Systems Magazine, vol. 18, pp. 26 – 41, Aug. 1998. [3] O. Lequin, M. Gevers, M. Mossberg, E. Bosmans and L. Triest, “Iterative Feedback Tuning of PID parameters: comparison with classical tuning rules”, Control Engineering Practice, vol. 11, pp. 1023 – 1033, Sept. 2003. [4] K. Hamamoto, T. Fukuda and T. Sugie, “Iterative Feedback Tuning of controllers for a two-mass-spring system with friction”, Control Engineering Practice, vol. 11, pp. 1061 – 1068, Sept. 2003. [5] R. Hildebrand, A. Lecchini, G. Solari and M. Gevers, “Optimal prefiltering in Iterative Feedback Tuning”, IEEE Transactions on Automatic Control, vol. 50, pp. 1196 – 1200, Aug. 2005. [6] H. Prochazka, M. Gevers, B. D. O. Anderson and C. Ferrera, “I.terative Feedback Tuning for robust controller design and optimization”, Proceedings of 44th IEEE Conference on Decision and Control and 2005 European Control Conference CDC-ECC’05, Seville, Spain, pp. 3602 – 3607, 2005. [7] W. Wang and Z. Hou, “IFT based design of DC double closed-loop speed tuning system”, Proceedings of 25th Chinese Control Conference, Harbin, China, pp. 1512 – 1516, 2006. [8] D. A. Bristow, M. Tharayil and A. G. Alleyne, “A survey of Iterative Learning Control”, IEEE Control Systems Magazine, vol. 26, pp. 96 – 114, June 2006. [9] M. Cho, Y. Lee, S. Joo and K. S. Lee, “Semi-empirical model-based multivariable Iterative Learning Control of an RTP system”, IEEE Transactions on Semiconductor Manufacturing, vol. 18, pp. 430 – 439, Aug. 2005. [10] J. -X. Xu, J. Xu and T. H. Lee, “Iterative learning control for systems with input deadzone”, IEEE Transactions on Automatic Control, vol. 50, pp. 1455 – 1459, Sept. 2005. [11] J. D. Ratcliffe, P. L. Lewin and E. Rogers, “Comparing the performance of two Iterative Learning Controllers with optimal feedback control”, Proceedings of IEEE International Symposium on Intelligent Control, Munich, Germany, pp. 838 – 843, 2006. [12] M. -S. Tsai, M. -T. Lin and H. -T. Yau, “Development of command-based Iterative Learning Control algorithm with consideration of friction, disturbance, and noise effects”, IEEE Transactions on Control Systems Technology, vol. 14, pp. 511 – 518, May 2006. [13] C. Ardelean, A. Graser, M. Mihajlov and R. -E. Precup, “Applications of Iterative Feedback Tuning in PI and PID Controller Design”, Buletinul Stiintific al Universitatii “Politehnica” din Timisoara, Transcations on Automatic Control and Computer Science, vol. 50 (64), no. 1, pp. 11 – 16, June 2005. [14] R. -E. Precup and S. Preitl, “Genetic Iterative Feedback Tuning (GIFT) method for fuzzy control system development”, Proceedings of 2nd International Symposium on Evolving Fuzzy Systems, Lake District, UK, pp. 148 – 153, 2006. [15] R. -E. Precup and S. Preitl, “Development method for low cost fuzzy controlled servosystems”, Proceedings of IEEE International Symposium on Intelligent Control, Munich, Germany, pp. 2707 – 2712, 2006. [16] D. H. Owens and J. Hätönen, “Iterative Learning Control – an optimization paradigm”, Annual Reviews in Control, vol. 29, pp. 57 – 70, June 2005. [17] S. Preitl, R. -E. Precup and C. Ardelean, “On a two-degree-of-freedom Iterative Feedback Tuning approach”, Proceedings of 7th International Conference on Technical Informatics CONTI’2006, Timisoara, Romania, vol. 1, pp. 19 – 24, 2006. [18] L. Horvath and I. J. Rudas, “Possibilities for application of associative objects with built-in intelligence in engineering modeling”, Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 8, pp. 544 – 552, Sept. 2004. [19] S. Kovacs and L. T. Koczy, “Application of interpolation-based fuzzy logic reasoning in behaviour-based control structures”, Proceedings of 2004 IEEE International Conference on Fuzzy Systems, Budapest, Hungary, vol. 3, pp. 1543 – 1548, 2004. [20] P. Baranyi, A. R. Varkonyi-Koczy and Z. Petres, “Reference signal following control design of the TORA system: a TP model transformation based approach”, Proceedings of 6th Portuguese Conference on Automatic Control CONTROLO 2004, Faro, Portugal, pp. 85 – 90, 2004. [21] P. T. Szemes, H. Hashimoto and P. Korondi, “Pedestrian-behavior-based mobile agent control in Intelligent Space”, IEEE Transactions on Instrumentation Measurement, vol. 54, pp. 2250 – 2257, Dec. 2005. [22] P. Baranyi, Z. Petres, P. L. Varkonyi, P. Korondi and Y. Yam, “Determination of different polytopic models of the prototypical aeroelastic wing section by TP model transformation”, Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 10, pp. 486 – 493, July 2006. [23] I. J. Rudas, B. Bede, H. Nobuhara and K. Hirota, “On approximation capability of pseudo-linear Shepard approximation operators”, Proceedings of 2006 IEEE International Conference on Fuzzy Systems, Vancouver, Canada, pp. 1292 – 1297, 2006. [24] W. P. Pedrycz, “Logic-based fuzzy neurocomputing with unineurons”, IEEE Transactions on Fuzzy Systems, vol. 14, pp. 860 – 873, Dec. 2006. |