Abstract
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 language | English (US) |
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Article number | 6495727 |
Pages (from-to) | 1890-1900 |
Number of pages | 11 |
Journal | IEEE Transactions on Circuits and Systems I: Regular Papers |
Volume | 60 |
Issue number | 7 |
DOIs | |
State | Published - 2013 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Hardware and Architecture
Keywords
- Evolutionary algorithms (EAs)
- Pareto front
- fuzzy estimator
- fuzzy networked system
- linear matrix inequality (LMI)
- multiobjective optimization problem (MOP)
- quantization error
- random delay
- source estimation