Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms

Flexible beam structure is usually applied in various fields of engineering and industrial. There are few points of interest using flexible structure and one of the advantages is that its lighter compared to a rigid structure. Besides that, flexible beam also can save cost, reduce energy consumption, and improve operation safety. However, flexible beam structures are too sensitive and susceptible to with unwanted vibration that would cause damage or degradation to the structure system. Hence, to overcome the problem, appropriate modelling and controller for such systems should be developed. Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). Therefore, two type of algorithms was used in this work for modelling development of flexible beam structure, which are ant colony optimization (ACO) and cuckoo search algorithm (CSA). Based on the comparative results, CSA achieved the lowest mean square error (MSE) value of 6.1547 x10(-9) meanwhile ACO recorded a MSE of 1.0728 x10(-8). Moreover, CSA was deduced to be the best model for flexible beam structure because it achieved 95 % confidence level in correlation test and has excellent stability in pole-zero diagram system. Thus, CSA is a suitable algorithm to represent the real behavior of flexible beam structure in a system.

Automated summary

Flexible beam structures are favored for being lighter and cost-effective compared to rigid structures, but are more susceptible to vibration. Researchers have developed various methods to suppress undesired vibration, with the cuckoo search algorithm (CSA) found to be the best model for representing the real behavior of flexible beam structures.