Fuzzy Robot Controller Tuning with Biogeography-Based Optimization

Thomas, George; Lozovyy, Paul; Simon, Dan

doi:10.1007/978-3-642-21827-9_33

Cited by 7 publications

(3 citation statements)

References 20 publications

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“…As with other EAs, BBO can be considered as a family of algorithms, or metaheuristic, and can be easily modified for application to various types of problems. BBO has been used for parameter selection in electric discharge machining [22], power flow optimization [23], robot control tuning [24], cancer classification [25], and many other applications.…”

Section: Biogeography-basedmentioning

confidence: 99%

Complex System Optimization Using Biogeography-Based Optimization

Simon

2013

Mathematical Problems in Engineering

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Complex systems are frequently found in modern industry. But with their multisubsystems, multiobjectives, and multiconstraints, the optimization of complex systems is extremely hard. In this paper, a new algorithm adapted from biogeography-based optimization (BBO) is introduced for complex system optimization. BBO/Complex is the combination of BBO with a multiobjective ranking system, an innovative migration approach, and effective diversity control. Based on comparisons with three complex system optimization algorithms (multidisciplinary feasible (MDF), individual discipline feasible (IDF), and collaborative optimization (CO)) on four real-world benchmark problems, BBO/Complex demonstrates competitive performance. BBO/Complex provides the best performance in three of the benchmark problems and the second best in the fourth problem.

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Section: Biogeography-basedmentioning

confidence: 99%

Complex System Optimization Using Biogeography-Based Optimization

Simon

2013

Mathematical Problems in Engineering

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“…We justify our use of BBO by noting that it outperforms many EAs on a variety of benchmarks (Simon, 2008), and some promising theoretical research has been done to support it, including an analysis of BBO's migration models (Ma and Simon, 2011), a theoretical comparison between BBO and GAs (Simon et al, 2011b), and a probabilistic study of BBO (Simon, 2011a). BBO Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/engappai has also been successfully applied to a variety of nonlinear control problems such as fuzzy logic-based robot path tracking control optimization, open-loop knee prosthesis control, and load dispatching in power systems (Thomas et al, 2011;Wilmot et al, 2013;Bhattacharya, 2010), and so it is reasonable to expect it to perform well for ICE control optimization.…”

Section: Introductionmentioning

confidence: 99%

Biogeography-based optimization of a variable camshaft timing system

Thomas

Simon

Michelini

2015

Engineering Applications of Artificial Intelligence

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Automotive system optimization Design and analysis of computer experiments a b s t r a c t Automotive simulations often prohibit the use of traditional optimization techniques because these simulations are complex and computationally expensive. These two qualities motivate the use of evolutionary algorithms and meta-modeling techniques respectively. In this work, we apply biogeography-based optimization (BBO) to optimize radial basis function (RBF)-based lookup table controls of a variable camshaft timing system for fuel economy. Also, we reduce computational search effort by finding an effective parameterization of the problem, optimizing the parameters of the BBO algorithm for the problem, and estimating the cost of a portion of the candidate solutions in BBO with design and analysis of computer experiments (DACE). We find that we can improve fuel economy by 1.7% over the original control parameters, and we find a tradeoff in population size, and an optimal value for mutation rate. Finally, we find that we can use a small number of samples to construct DACE models, and we can use these models to estimate a significant portion of the candidate solutions each generation to reduce computation effort and still obtain good BBO solutions.

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“…In that study, the results obtained from the BBO method were promising. In addition to this, the BBO method has been successfully applied to different areas, such as aircraft image classification [13], image segmentation [14], power flow problems [15], the economic load dispatch problem [16,17], engine sensor selection [11], robot controllers [18] and the traveling salesman problem [19]. This paper focuses on optimizing the control parameters of the PID controller for the AVR system using the BBO method.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of biogeography-based optimization for automatic voltage regulator system

Güvenç¹,

Yi̇ği̇t²,

Işık³

et al. 2016

Turk J Elec Eng & Comp Sci

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A self-tuning method to determine the appropriate parameters of a proportional-integral-derivative controller for an automatic voltage regulator (AVR) system using a biogeography-based optimization (BBO) algorithm is proposed in this study. The BBO algorithm was developed based on the theory of biogeography, which describes migration and its results. We propose that the BBO algorithm has a high-quality solution and stable convergence characteristics, and thus it improves the transient response of the controlled system. The performance of the BBO algorithm depends on the transient response, root locus, and Bode analysis. Robustness analysis is done in the AVR system, which is tuned by an artificial bee colony (ABC) algorithm in order to identify its response to changes in the system parameters. We compare the BBO algorithm with the ABC algorithm, particle swarm optimization algorithm, and differential evolution algorithm. The results of this comparison show that the BBO algorithm has a better tuning capability than the other optimization algorithms.

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Fuzzy Robot Controller Tuning with Biogeography-Based Optimization

Cited by 7 publications

References 20 publications

Complex System Optimization Using Biogeography-Based Optimization

Complex System Optimization Using Biogeography-Based Optimization

Biogeography-based optimization of a variable camshaft timing system

Performance analysis of biogeography-based optimization for automatic voltage regulator system

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