Actuator placement optimization in an active lattice structure using Generalized Pattern Search and verification

Abstract

Shape morphing structures are actively used in the aerospace and automotive industry. By adapting their shape to a stimulus such as heat, light, or pressure, a design can be optimized to achieve a broader band of functionality over its lifetime. The quality of a structure with respect to shape-morphing can be assessed using five criteria: weight, load-carrying capacity, energy consumption, accuracy of the controlled deformation, and the range and number of achievable target shapes. This work focuses on the use of lightweight and stiff active lattice structures, where the layout of actuators within the structure determines the final deformation. It uses a statically and kinematically determinate Kagome lattice pattern that has been shown to deform the most accurately with the least energy. The use of a determinate structure justifies the implementation of a simplified deformation model. The deformation resulting from a given actuator layout can be expressed as a linear combination of the deformation of individual actuators, which are all computed in a pre-processing step and expressed with an influence matrix. The actuator layout is thus optimized for several target shapes. The linear combination model is shown to replicate FEM simulations with an average of 94.8% accuracy for all target shapes. The actuator layouts in one-level lattices are tested using a novel design for a 3D printed modular Kagome pneumatic lattice structure. The experimental results replicate the target shapes with an average accuracy of 79.9%. The resulting actuator layouts are shown to form more target shapes with a similar deformation range as similar publications.