A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters

被引:21
|
作者
Pelusi, Danilo [1 ]
Mascella, Raffaele [1 ]
Tallini, Luca [1 ]
机构
[1] Univ Teramo, Fac Commun Sci, I-64100 Teramo, Italy
关键词
optimization algorithms; IIR filters; gravitational search algorithm; fuzzy systems; PARTICLE SWARM OPTIMIZATION; MODULAR NEURAL-NETWORKS; DIFFERENTIAL EVOLUTION; PRESCRIBED MAGNITUDE; DIGITAL-FILTERS; ROBUST STABILITY; LOGIC; ADAPTATION; GSA;
D O I
10.3390/en11040736
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The goodness of Infinite Impulse Response (IIR) digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA). In this way, a Fuzzy Gravitational Search Algorithm (FGSA) is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE) and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.
引用
收藏
页数:18
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