The stability analysis of Bat Algorithm

Papliński, Janusz P.; Łazoryszczak, M.

doi:10.1109/inista.2017.8001133

Cited by 2 publications

(7 citation statements)

References 22 publications

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“…The Lyapunov theory defines the necessary and sufficient conditions for absolute stability of nonlinear and/ or time-varying systems. Any simplifications are not needed during stability analysis, which is important because the obtained results are more reliable than the results from the previous work [22]. Both methods give the similar solution, then the present paper confirms the correctness of simplicity used in preceding work [22].…”

Section: Introductionsupporting

confidence: 83%

“…There are some stability analyses of PSO algorithm based on the location of the roots [16][17][18] and the Lyapunov function [19][20][21]. We made a similar study for BA in [22].…”

Section: Introductionmentioning

confidence: 99%

“…The present paper is the extended version of the conference paper [22] published in INnovations in Intelligent Sys-Tems and Applications (INISTA) 2017. The way of the approach presented in the paper is largely new and much more general.…”

Section: Introductionmentioning

confidence: 99%

“…Then the use of a description in the form of the state-space and checking the controllability and observability allow reducing the order of dynamic. The method of stability analysis proposed in [22] is based on the location of the roots of the difference equation which is appropriate for linear time-invariant systems. This method was used after omitting the randomness of parameters and treatment of the algorithm as stationary.…”

Section: Introductionmentioning

confidence: 99%

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Stability Analysis of the Bat Algorithm Described as a Stochastic Discrete‐Time State‐Space System

Papliński

2018

Complexity

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The main problem with the soft-computing algorithms is a determination of their parameters. The tuning rules are very general and need experiments during a trial and error method. The equations describing the bat algorithm have the form of difference equations, and the algorithm can be treated as a stochastic discrete-time system. The behaviour of this system depends on its dynamic and preservation stability conditions. The paper presents the stability analysis of the bat algorithm described as a stochastic discrete-time state-space system. The observability and controllability analyses were made in order to verify the correctness of the model describing the dynamic of BA. Sufficient conditions for stability are derived based on the Lyapunov stability theory. They indicate the recommended areas of the location of the parameters. The analysis of the position of eigenvalues of the state matrix shows how the different values of parameters affect the behaviour of the algorithm. They indicate the recommended area of the location of the parameters. Simulation results confirm the theory-based analysis.

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Section: Introductionsupporting

confidence: 83%

“…There are some stability analyses of PSO algorithm based on the location of the roots [16][17][18] and the Lyapunov function [19][20][21]. We made a similar study for BA in [22].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stability Analysis of the Bat Algorithm Described as a Stochastic Discrete‐Time State‐Space System

Papliński

2018

Complexity

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“…The movement of the real bat is assumed as virtual bat in this model. Its maximum loudness and minimum loudness are assumed as A max and A min respectively [3]. At any instant of time its position, velocity, and frequency are represented as x i , v i and f i respectively.…”

Section: Bat Algorithmmentioning

confidence: 99%

Design and Development of Adaptive Fuzzy Control System for Power Management in Residential Smart Grid Using Bat Algorithm

Viknesh¹,

Sivaram²

2018

Technol Econ Smart Grids Sustain Energy

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An adaptive fuzzy logic control system was designed for the management of power in smart grid. The system was developed using BAT algorithm. This paper analyses the approach of adaptive fuzzy logic system accompanied with bat algorithm in power management of smart grid. The path of carrying information i.e. communication layer between users and the energy provider in smart grid is analyzed. To achieve this, behavior of bats and its algorithm is studied and compared with vectors in adaptive fuzzy logic system and applied in power utility side of smart grid. It helps in indicating peak in load and also helps in prediction of power consumption in users. The offline algorithm is developed, simulated using Matlab 16a and simulation results are evaluated.

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The stability analysis of Bat Algorithm

Cited by 2 publications

References 22 publications

Stability Analysis of the Bat Algorithm Described as a Stochastic Discrete‐Time State‐Space System

Stability Analysis of the Bat Algorithm Described as a Stochastic Discrete‐Time State‐Space System

Design and Development of Adaptive Fuzzy Control System for Power Management in Residential Smart Grid Using Bat Algorithm

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