Dynamic Morphing of Smart Trusses and Mechanisms Using Fuzzy and Neuro-Fuzzy Techniques

Abstract

In the present investigation, the principles of dynamic morphing of smart truss structures and mechanisms are discussed. A possible way in order to find the optimal geometry of the structure for the enhancement of structural performance in terms of vibration control is sought. The vibrations of the host dynamic structures are monitored by controllers which are based on the principles of Mamdani-type fuzzy inference and Sugeno-type adaptive neuro-fuzzy inference. More specifically, the objective of the present study is a design, tuning, and an application of robust intelligent control mechanisms by means of the suppression of structural vibrations for several types of excitation forces. The proposed models are discretized by using a finite element method. For the time integration of the equations of motion, the Newmark-β method is used. The calculations and the analysis are conducted within the Matlab environment by using the Adaptive Neuro-Fuzzy Inference System (ANFIS) tool, which is included in the fuzzy toolbox. The controllers are tested with different excitation forces applied on a truss-shaped structure. The control outputs are applied on each time of the simulation in order to achieve the lowest possible deformation and to prevent potential damage or corruption of the structure. The same principles are used for the dynamic morphing of structures and mechanisms. The proposed formulation can be applied, among many others, on smart irrigation systems such as spray booms, on radio-telescope bases, on the spars of smart wings, on aircraft wings etc.

Progress and recent trends in generative design

“…The new design stability will be tested by using a FEA analysis which is the appropriate tool to test a wide range of structures [18]. Results related to the design of controlled flexible structures can be founr in [19][20]…”