Publication | Open Access
Ant Colony Based Model Prediction of a Twin Rotor System
24
Citations
9
References
2012
Year
EngineeringAerospace EngineeringFirefly AlgorithmIntelligent OptimizationMechatronicsMechanical SystemsSystem OptimizationComputer EngineeringSystems EngineeringRotor DynamicHybrid Optimization TechniqueTwin Rotor SystemModeling And SimulationBiologically-inspired Optimization TechniquesAnt Colony OptimizationAnt Colony
Interest in biologically-inspired optimization techniques has increased due to its accurate results, fast performance and ease of use. In this paper, an ant colony optimization (ACO) technique is deployed and used for modelling a twin rotor system. The system is perceived as a challenging engineering problem due to its strong cross coupling between horizontal and vertical axes and inaccessibility of some of its states and outputs for measurements. Accurate modelling of the system is thus required so as to achieve satisfactory control objectives. It is demonstrated that ACO can be effectively used for modelling the system with highly accurate results. The accuracy of the modelling results is demonstrated through validation tests including training and test validation and correlation tests.
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