Expert Systems with Applications: An International Journal
Adaptive computational chemotaxis in bacterial foraging optimization: an analysis
IEEE Transactions on Evolutionary Computation
EMS '09 Proceedings of the 2009 Third UKSim European Symposium on Computer Modeling and Simulation
Bacterial Foraging Algorithm with Adaptable Chemotactic Step Size
CICSYN '10 Proceedings of the 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks
A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
This paper presents current work on biologically-inspired optimisation techniques based on bacterial foraging algorithms (BFAs) and their application to modelling of a single-link flexible manipulator. The objective of this work is to develop a single-link flexible manipulator model based on modified BFAs. First, three adaptation mechanisms of the chemotactic step size mechanism of BFA are proposed. New approaches of adaptable chemotactic step size are based on linear, quadratic and exponential functions of cost function value. Then, these three adaptive BFAs are used to develop three single-input single-output models to characterise a flexible manipulator from torque input to hub-angle, hub velocity and end-point acceleration responses. The performances of the adaptive BFAs are compared to that of standard BFA based on convergence to optimum value, the optimum value achieved and time-domain and frequency domain responses of the developed models.