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Contribution to Book
Biogeography-Based Optimization for Robot Controller Tuning
Computational Modeling and Simulation of Intellect: Current State and Future Perspectives
  • Paul Lozovyy, Cleveland State University
  • George Thomas, Cleveland State University
  • Daniel J. Simon, Cleveland State University
Document Type
Contribution to Books
Publication Date
1-1-2011
Abstract
This research involves the development of an engineering test for a newly-developed evolutionary algorithm called biogeography-based optimization (BBO), and also involves the development of a distributed implementation of BBO. The BBO algorithm is based on mathematical models of biogeography, which describe the migration of species between habitats. BBO is the adaptation of the theory of biogeography for the purpose of solving general optimization problems. In this research, BBO is used to tune a proportional-derivative control system for real-world mobile robots. The authors show that BBO can successfully tune the control algorithm of the robots, reducing their tracking error cost function by 65% from nominal values. This chapter focuses on describing the hardware, software, and the results that have been obtained by various implementations of BBO.
DOI
10.4018/978-1-60960-551-3
Citation Information
P. Lozovyy, G. Thomas, and D. Simon, “Biogeography-Based Optimization for Robot Controller Tuning,” in Computational Modeling and Simulation of Intellect (B. Igelnik, editor) IGI Global, pp. 162-181, 2011