A multiobjective approach for source estimation in fuzzy networked systems

Wei Yu Chiu, Bor Sen Chen, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


In this paper, fuzzy networked systems with a randomly varying delay and quantization errors are considered to represent signal transmission systems of nonlinearly interactive sources. A source estimation scheme is proposed by using a multiobjective approach, addressing the concerns of estimation errors and transmission power consumption. A mixed H2/H design is employed to enhance the estimation performance, while the number of quantized bits is optimized to reduce the power consumption. A Pareto front representation is adopted so that the proposed estimation scheme is designed from a broader perspective in contrast with the conventional single-objective approach. It turns out that the proposed source estimator parameters can serve as decision variables of a multiobjective optimization problem (MOP) with linear matrix inequality constraints. This MOP can be solved by using deterministic algorithms, such as interior-point methods, for solutions of internal variables and using stochastic algorithms, such as multiobjective evolutionary algorithms, for the global optimality. Numerical examples are provided to illustrate the proposed methodology.

Original languageEnglish (US)
Article number6495727
Pages (from-to)1890-1900
Number of pages11
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Issue number7
StatePublished - 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Hardware and Architecture


  • Evolutionary algorithms (EAs)
  • Pareto front
  • fuzzy estimator
  • fuzzy networked system
  • linear matrix inequality (LMI)
  • multiobjective optimization problem (MOP)
  • quantization error
  • random delay
  • source estimation


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