A near-optimal-trim-search method for six-degrees-of-freedom model insects: An application to flight in the lateral-wind condition

Abstract

This paper presents an improved trim-search method for six-degrees-of-freedom (6-DOF) flapping-wing insects and its application to flight in the lateral-wind condition. A multibody-dynamics (MBD) code was developed and coupled with an extended unsteady vortex-lattice method (UVLM) to create a flapping-flight simulation framework. Using artificial neural networks (ANNs) and the genetic algorithm (GA), the trim-search method was developed to provide a near-optimal solution. The paper shows that the required power of the trim solution obtained by the present method is less than that from the conventional one. Based on the research results, the paper has revealed how a model insect can respond to sustain their hovering flight state in the lateral-wind condition. In general, the insect has to change its left- and right-wing kinematic parameters asymmetrically. The most noticeable differences between the kinematic parameters of the two wings are found in the sweep and rotation amplitudes. The research also showed an increase in the required power of the windward wing and a decrease in that of the leeward wing. However, the total required power generally grows due to the lateral wind.