Advanced Composites Manufacturing and Repair Using Integrated Distributed Actuation and Dynamic Network Control

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Because of their high stiffness and light weight, composites such as carbon-fiber reinforced polymers are finding increased use in the automotive, aerospace, and marine transportation sectors and in renewable energy systems such as large wind turbines. An important step in the manufacture of many composites is high-temperature curing, which involves cycling the part through a precise temperature sequence in a sealed pressure vessel called an autoclave. This project focuses on the joining of these finished individual parts to form a complete product. While mechanical fasteners or low-temperature adhesives have inferior performance to high-temperature composite bonds, the assembled system is far too large to place in an autoclave as a unit. This project considers the use of embedded heaters distributed throughout the joint to execute the necessary thermal cycle. So as not to compromise the integrity of the structure, these heaters are made using the same carbon-fiber material as the rest of the composite structure. In preliminary tests this approach has produced joints that equal autoclaved parts in quality; the challenge addressed by this project is achieving such a result over a large, complex structure, such as an airplane wing. This will be done by repurposing advanced control techniques originally developed for networks of dynamic systems, such as mobile robots. The same approach may be used to repair damaged or fatigued composite systems, economically and sustainably extending the useful life of expensive infrastructure. The most advanced technology is useless without a trained workforce capable of employing it. This project will provide training and education to undergraduate and graduate students in advanced manufacturing and controls, and the results will be used in outreach and recruitment to high-school students.A network of multiple distributed heaters that can account for variations in heat loss, e.g., due to uneven sub-structures, and enable uniform temperatures at the bondline for consistent curing of the adhesive are planned. The control challenge arises from differences in the thermal dynamics of each of the distributed heater system (input voltage to local temperature) in the network due to differences in material properties (e.g., thickness of composites) and boundary conditions (e.g., due to the presence of substructures). Current iterative approaches for networked multi-agent systems are mostly applicable to homogenous agent dynamics. It is challenging to prove convergence of iterative learning for heterogeneous, networked multi-agent systems when the dynamics of the different agents are general linear systems. A novel inversion-based iterative control is planned that can correct for the dynamics of each agent and, thereby, can achieve the desired output specified through the network. The intellectual merit of the research is to develop conditions that quantify the acceptable modeling uncertainty for ensuring convergence of iterative approaches in the presence of heterogeneity. Thus, the research will advance the state-of-the-art in iterative-learning theory for networked multi-agent systems and its applicability to important technological problems such as manufacturing.