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Improved Bacterial Foraging Strategy for Controller Optimization Applied to Robotic Manipulator System
- Source :
- IEEE International Symposium on Intelligent Control.
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
Abstract
- During the course of evolution, colonies of ants, bees, wasps, bacteria and termites have developed sophisticated behavior, intricate communication capabilities, decentralized colony control, group foraging strategies and a high degree of worker cooperation when tackling tasks. Utilizing these capabilities, any bio-inspired optimization techniques using analogy of swarming principles and social behavior in nature — swarm intelligence — have been adopted to solve a variety of engineering and robotics problems. In this paper, new approaches of bacterial colony optimization method with variable speed based on uniform, Gaussian, and Cauchy probability distribution were tested. Bacterial colony, a swarm intelligence methodology, is evaluated for a problem of optimization of a PID (proportional-integral-derivative) multivariable controller. The simulation results are compared with classical bacterial colony approach with constant velocity for a case study of control of a robotic manipulator system with two degree of freedom.
- Subjects :
- Engineering
business.industry
Ant colony optimization algorithms
MathematicsofComputing_NUMERICALANALYSIS
PID controller
Particle swarm optimization
Robotics
Control engineering
ComputingMethodologies_ARTIFICIALINTELLIGENCE
Swarm intelligence
Control theory
Control system
Robot
Artificial intelligence
business
Metaheuristic
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- IEEE International Symposium on Intelligent Control
- Accession number :
- edsair.doi.dedup.....145f7980e07d5f68a4c7ff1a3ddac701