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An improved MOCC with feedback control structure based on preference

Published:12 June 2009Publication History

ABSTRACT

The optimal solution of multi-objective control problem (MOCP) isn't unique, so it is hard for traditional method to obtain these optimal solutions in one simulation process. Based on this background, Multi-Objective Compatible Control (MOCC) algorithm was presented by Lihong Xu in [2]. MOCC is a compromise method, which hunts for suboptimal and feasible region as the control aim rather than precise optimal point. The controller of MOCC is optimized by GA in its interval, namely its controller lacks concrete controller structure. Due to the controller without concrete structure, the system model must be accurate and without input disturbance; however, it is impractical in practice. Besides, the control problem is different from the optimization. Different user has different preference and users' preference information plays a key role in control performance. In this paper, the feedback control law and users' preference information are incorporated into MOCC algorithm. An improved MOCC (IMOCC) algorithm is presented. The simulation result demonstrates its superiority and advantage over the MOCC algorithm.

References

  1. Lihong Xu, Bingkun Zhu, Controller Design of Conflict Multi-objective UKACC 2008, England.Google ScholarGoogle Scholar
  2. Lihong Xu, Zhiqiang Zou, and Qingsong Hu, Two-Layer Optimization Compatible Control for Multi-Objective Control Systems, IEEE International Conference on Networking, Sensing and Control, 23--25 April, 2006, pp.658--663.Google ScholarGoogle Scholar
  3. Lihong Xu, Qingsong Hu and Erik Goodman. Two layer Iterative Multi-objective Compatible Control algorithm. the 46th IEEE Conference on Decision and Control,2007, pp2992--2997.Google ScholarGoogle Scholar
  4. Masaaki, I. (1997), Multi-objective optimal control through linear programming with interval objective function, SICE, July 29--31, Tokushima, pp. 1185--1188.Google ScholarGoogle Scholar
  5. Rangan, S. & Poolla, K.(1997), Weighted optimization for multi-objective full-information control problems, System & Control Letter, Vol.31, pp. 207--213. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Eisenhart, K. J. (2003), Multi-objective optimal control problems with endpoint and state constraint, Ph.D. thesis, Western Michigan University.Google ScholarGoogle Scholar
  7. Iskander M. G.(2003), Using different dominance criteria in stochastic fuzzy linear multi-objective programming: A case of fuzzy weighted objective function, Mathematical and Computer Modeling, Vol. 37,pp. 67--176. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Zhao, Z., Yasuyuki, I. & Masatoshi, N.(2003), Diffuser multi-objective control for STEC plant, IEEE Conference on Systems, Man and Cybernetics, October 5--8, 2003, pp. 148--153.Google ScholarGoogle Scholar
  9. Masaaki, I. (1997), Multi-objective optimal control through linear programming with interval objective function, SICE, July 29--31, Tokushima, pp. 1185--1188.Google ScholarGoogle Scholar
  10. Scherer,C.W.(1995), Multi-objective Control, IEEE Transaction on Automatic Control, vol. 40, pp. 1054--1061.Google ScholarGoogle ScholarCross RefCross Ref
  11. Scherer, C, Gahinet P. & Chilali, M.(1997), Multi-objective output feedback control via LMI Optimization, IEEE Transactions on Automatic Control, vol. 42, pp. 896--911.Google ScholarGoogle ScholarCross RefCross Ref
  12. Kalyanmoy Deb (2002), Multi-Objective Optimization using Evolutionary Algorithms, JOHN WILEY & SONS, LTD, pp. 235--237Google ScholarGoogle Scholar

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      cover image ACM Conferences
      GEC '09: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
      June 2009
      1112 pages
      ISBN:9781605583266
      DOI:10.1145/1543834

      Copyright © 2009 ACM

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      Publication History

      • Published: 12 June 2009

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