FEA model based cautious automatic optimal shape control for fuselage assembly

In a half fuselage assembly process, shape control is vital for achieving ultra-high precision assembly. To achieve better shape adjustment, we need to determine the optimal location and force of each actuator to push and pull a fuselage to compensate for its initial shape distortion. The current practice achieves this goal by solving a surrogate model based optimization problem. However, there are two limitations of this surrogate model based method: (1) Low efficiency: Collecting training data for surrogate modeling from many FEA replications is time-consuming. (2) Non-optimality: The required number of FEA replications for building an accurate surrogate model will increase as the potential number of actuator locations increases. Therefore, the surrogate model can only be built on a limited number of prespecified potential actuator locations, which will lead to sub-optimal control results. To address these issues, this paper proposes an FEA model based automatic optimal shape control (AOSC) framework. This method directly loads the system equation from the FEA simulation platform to determine the optimal location and force of each actuator. Moreover, the proposed method further integrates the cautious control concept into the AOSC system to address model uncertainties in practice. The case study with industrial settings shows that the proposed Cautious AOSC method achieves higher control accuracy compared to the current industrial practice.

Optimal Shape Control of Piezoelectric Intelligent Structure Based on Genetic Algorithm

Shape variation induced by mismachining tolerance, humidity and temperature of the working environment, material wear and aging, and unknown external load disturbances have a relatively large influence on the dynamic shape of a mechanical structure. When integrating piezoelectric elements into the main mechanical structure, active control of the structural shape is realized by utilizing the inverse piezoelectric effect. This paper presents a mathematical model regarding piezoelectric intelligent structure shape control. We also applied a genetic algorithm, and given a piezoelectric intelligent cantilever plate with both ends affected by a certain load, optimal shape control results of piezoelectric materials were analyzed from different perspectives (precision reference or cost reference). The mathematical model and results indicate that, by optimizing a certain number of piezoelectric actuators, high-precision active shape control can be realized.