Artificial intelligence control of a supersonic jet based on linear genetic programming (LGP)
Implementing Organization
Indian Institute of Technology Kanpur
Principal Investigator
Dr. Arun Kumar Perumal
Indian Institute of Technology Kanpur
Project Overview
Supersonic aircraft require control of thrust direction for various applications, including manoeuvrability and survivability. To meet these needs, new flow control techniques are being developed, with fluidic thrust vectoring (FTV) methods being particularly important. This project aims to develop an active control technique for flow control based on FTV, using linear genetic programming to identify the optimal conditions of injectors. Thrust vectoring studies will be performed on a Mach 1.85 jet with 8 evenly spaced injectors with varying diameters. The fluid parameters for optimization include injector location, injector number, mass flow rate ratio, and velocity ratio. However, characterization studies on these parameters are necessary for every injector diameter, stifling progress towards implementing this technology. A novel linear genetic programming will be developed to identify the optimal conditions of injectors, mainly focusing on injector location, number, and volume.