Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

Abstract

This paper introduces a CPS application for intelligent aeroplane assembly. At first, the CPS structure is presented, which acquires the characteristics of general CPS and enables "simulation-based planning and control" to achieve high level intelligent assembly. Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling, respectively. The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation, and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration, it can also directly link to data, and the error is smaller. This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control. A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness. At the same time, an outer collaborative trajectory planning is also designed. All the experiment results show the feasibility of above proposed methods.

Modeling and Key Technologies of Intelligent Assembly System for Mechanical Products

“…The center of formula ( 8) is the number of input MCIIRi of intelligent control resource MCIIRi, n o_i is the quantity of output MCIIRi of intelligent control resource MCIIRi, n I_i + n O_i = n m_i , so according to formula (7) and formula (8), the calculation formula of intelligent control resource MCIIRi configuration is obtained, such as Formula (9): Hc= H s_c_s H i_c = log 2 1X log 2 n m_i P in_i log 2 P in_i XP out_i log 2 P out_i (9) According to the definition of information droplets and the definition of the intrinsic entropy of the mechanical assembly unit, MIOT-IAUM's resource allocation entropy metric is shown in (10), where P s_s_i is the intelligent management resource MCIIRi in the mechanical product intelligent assembly unit MIOT-IAUM The entropy weight in .…”

“…In order to adapt to the complex and changeable market environment, countries have put the development of new technology-driven intelligent manufacturing at the core of national industrial development strategy [9]. Manufacturing industry in our country belongs to the one of pillar industries, machinery industry to provide technology and equipment for the whole national development, the development of national economy and the progress of science and technology has a decisive role, therefore, the development and application in mechanical assembly intelligent assembly system, will certainly to promote the development of mechanical manufacturing, further liberation and development of the productive forces has important value [10].…”