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.

A nonlinear optimization method for large shape morphing in 3D printed pneumatic lattice structures

“…Since pneumatic actuators function as a closed compressed air system, they do not suffer the energy losses of SMAs/SMPs, motors, and piezos related to heat. Previous work by the authors [5] showed structures achieving several 2.5D target shapes with a deformation range on par with similar work using electromechanical actuation. Thus, this work will use 3D printed pneumatic actuators, as they best address all five criteria of shape morphing outlined above.…”

“…There are five criteria to assess the quality of a shape morphing design: weight, load-carrying capacity, energy consumption, accuracy of the controlled deformation, and the range and number of deformation modes [2]. The two first criteria are often addressed with the use of lattice structures, since they are light, stiff, and straightforward to optimize [2][3][4][5]. Energy consumption can be addressed by choosing an actuation method which requires little energy by reducing the force needed to actuate a structure.…”

“…In the cases where it has been validated, shape morphing has been demonstrated experimentally with the following actuation methods: shape memory alloys (SMAs) [8][9][10][11] or polymers (SMPs) [9,12,13], electromechanical components such as servo and stepper motors [14][15][16][17], and piezoelectric stacks. Previous work from the authors also introduced pneumatic linear actuators for 2D and 2.5D shape morphing structures [5,18].…”

“…In a preliminary step, the search space for shape morphing lattices is analyzed and used to determine the most appropriate optimization method for actuator placement in a lattice structure. The first contribution of this work is the design of a new modular 3D printed joints to build 2D and 3D shape morphing lattice structures, using equally 3D printed pneumatic actuators previously shown in [5]. The second contribution of this work is to assess the accuracy of the chosen method in achieving several target shapes, both in 2D and 3D, using an finite element analysis (FEA) and a modular lattice toolkit to verify the results.…”

Deformation control method for active shape morphing lattice structure using topology optimization approach

“…However, this system necessitates a complex drive system. Du Pasquier and Shea [23] optimized the layout of actuators for various target shapes within a Kagome lattice using genetic algorithms. They experimentally validated the optimization results with the lattice structure controlled by pneumatic linear actuators.…”