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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 10    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 10, October 2011 Edition
Control and System Identification via Swarm and Evolutionary Algorithms
Full Text(PDF, 3000)  PP.  
Tayebeh Mostajabi, Javad Poshtan
adaptive control; evolutionary algorithm; global minimum, local minima, robotics; swarm intelligence; system identification.
A central topic of swarm intelligence is the investigation of different types of emergent collective behaviors in swarms. This article focus on the swarm intelligence applications in control and system identification. Particle swarm optimization (PSO), a novel population based stochastic optimizer with fast convergence speed and simple implementation and genetic algorithm, have been successfully applied to solve system identification optimization problems. In addition, PSO and ant colony optimization (ACO) have been applied as a navigation algorithm in swarm robots. Some of the recently proposed swarm based metaheuristics such as bacterial foraging optimization algorithm (BFOA), wasp optimization algorithm (WOA), bee optimization algorithm (BOA) and Physarum Solver will need further investigation to assess their potential for generating state-of-the-art algorithms that are useful for this area
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