Modeling of higher order systems using artificial bee colony algorithm

Bağış, Aytekin; Senberber, Halit

doi:10.11121/ijocta.01.2016.00298

Cited by 5 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While scaling factor (F) 0.8, crossover rate is selected as 0.9 for the DEA, the limit value is defined according to the expression of [(colonies size x number of parameter)/2] for ABC algorithm. The Gmi and Gmf terms in the figures represent the integer and fractional models given in (4) and 5, respectively.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…While (4) belongs to the integer order model (Gm1), (5) defines a fractional order model (Gm2). Thus, five parameters (a0, a 1 , a 2, b 0 and L) for the (4) and seven parameters (a 0 , a 1 , a 2, b 0 , L, k 1 and k 2 ) for the (5) are optimized. In the modelling process for two systems (G 1 [33] and G 2 [34]) from the literature, the model parameters have been determined by using DE and ABC algorithms.…”

Section: A Definition Of the Modelling Problemmentioning

confidence: 99%

“…Learning of internal structure that characterizes the system by using experimental or mathematical data is called as system modelling [1]- [4]. The main purpose of the system modelling is to reflect the characteristics of the system using lower order process in general.…”

Section: Introductionmentioning

confidence: 99%

“…Mete et al [5] presented system modelling based on cascade of a nonlinear second order volterra (SOV) model and a linear FIR model using DE algorithms. Another study which is examination of ABC algorithm performance in the modelling of higher order systems is presented by Bagis and Senberber [4]. In the study of Deng, a system modelling approach based on PSO algorithm is reported [6].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

ABC Algorithm Based System Modelling for Tuning the Fractional Order PID Controllers

Senberber¹,

Bağış²

2018

ElAEE

Self Cite

View full text Add to dashboard Cite

The effectiveness of the model structure for designing control system is highly depending on the right selection of tuning parameters belonging of the algorithms. No doubt, preferable parameter estimation leads to better results for the modelling process. This study consists of two main parts. In the first part, fractional and integer model structures with time delay are proposed for integer-order systems using artificial bee colony (ABC) algorithm and differential evolution (DE) algorithm. The second part of the study is the fractional order PID controller design based on the use of new models obtained with the help of Matlab/Simulink software package. While the integrated square error (ISE) is preferred in the modelling process as the performance criterion, four different performance indices are chosen as ISE, integral time-square error (ITSE), integral absolute error (IAE) and integral timeweighted absolute error (ITAE) during the controller design phase. It is shown that, the results obtained with fractional modelling have achieved better results than the integer order modelling. Furthermore, the controller designs for the algorithm based models proposed in the first stage of the study present a satisfactory performance.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Section: A Definition Of the Modelling Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

ABC Algorithm Based System Modelling for Tuning the Fractional Order PID Controllers

Senberber¹,

Bağış²

2018

ElAEE

Self Cite

View full text Add to dashboard Cite

show abstract

“…One of the quite successful optimization algorithms is the artificial bee colony (ABC) algorithm presented by Karaboga [29], [31]- [33]. This population based approach presents efficient solutions for numerical optimization problems especially.…”

Section: Algorithms Used In Study a Abc Algorithmmentioning

confidence: 99%

ABC Algorithm Based PID Controller Design for Higher Order Oscillatory Systems

Bağış¹,

Senberber²

2017

ElAEE

Self Cite

View full text Add to dashboard Cite

This paper presents the results of an investigation based on the use of artificial bee colony (ABC) algorithm to determine the optimum PID parameters for higher order oscillatory systems. For this aim, several oscillatory systems with different orders from the literature were selected. In order to achieve the desired closed loop system response, the PID parameters were tuned by the ABC algorithm using an appropriate objective function. To demonstrate the effectiveness of the considered approach, performance of the ABC algorithm was compared with that of the conventional PID tuning methods given in the literature and two popular heuristic optimization algorithms namely particle swarm optimization (PSO) algorithm and genetic algorithm (GA).

show abstract

Fractional PID controller design for fractional order systems using ABC algorithm

Senberber

Bağış

2017

2017 Electronics

View full text Add to dashboard Cite

Modeling of higher order systems using artificial bee colony algorithm

Cited by 5 publications

References 21 publications

ABC Algorithm Based System Modelling for Tuning the Fractional Order PID Controllers

ABC Algorithm Based System Modelling for Tuning the Fractional Order PID Controllers

ABC Algorithm Based PID Controller Design for Higher Order Oscillatory Systems

Fractional PID controller design for fractional order systems using ABC algorithm

Contact Info

Product

Resources

About