“With Model-Based Design, we know that if we simulate correctly, the UAV will fly correctly. “A single flight test can cost more than $10,000,” says Moon. “Model reuse, code generation, and reduced testing times with Model-Based Design cut development engineer-hours by 60%.”Ĭostly flight tests minimized. “The software we developed with MATLAB and Simulink had more functionality and verification coverage than projects that we hand-coded,” Moon says. “Polyspace found dozens of divide-by-zero and overflow errors in our handwritten code, and proved the absence of run-time errors in code generated by Embedded Coder.”ĭevelopment effort reduced by 60%. “Polyspace Code Prover is crucial for the development of safe software and eliminating critical errors that could occur in flight,” says Moon. Resultsġ00% of run-time errors in handwritten code identified and eliminated. Korean Air completed development on schedule, and the UAV has received airworthiness certification from the Korean government. Korean Air engineers provided certification authorities with MC/DC coverage reports generated by Simulink Check and Simulink Coverage and testing reports generated by Polyspace Code Prover. The HIL model, which contains more than 11,000 blocks in the flight control and flight dynamics submodels, was reused to create an operator training simulator for the UAV. The team conducted real-time HIL simulations with Simulink Real-Time™. No run-time errors were found in the generated code. Using Polyspace Code Prover™, the team checked all the code for run-time errors, identifying several in the handwritten code that they subsequently corrected. They integrated this C code with code they had handwritten for hardware drivers, and they reused test cases for model coverage to measure 100% MC/DC code coverage. The team generated more than 45,000 source lines of code from their models with Embedded Coder ®. Using Simulink Check™ and Simulink Coverage™, the engineers performed regular checks to ensure the model complied with the company’s modeling standards (based on MAAB guidelines) and to measure 100% MC/DC model coverage for their test suite.
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The flight management and control system, including the automatic landing guidance subsystem, was modeled in Simulink and Stateflow ®.Īfter running desktop simulations to verify the flight control laws and collect control response data, they analyzed the results, and later, flight test results, in MATLAB ®. The team designed flight control laws using Robust Control Toolbox™ and Control System Toolbox™ to compute optimal control gains. Later they used System Identification Toolbox™ to estimate model parameters for flight dynamics and performance verification. The engineers developed a dynamic model of the UAV, including landing gear dynamics for simulating automated take-off and landing, with Aerospace Blockset™. In the early phases of development, the engineers developed a Simulink ® model to refine and validate high-level requirements. Zuo L, Zhang X, Li Z et al (2023) Design of UAV control law based on active disturbance rejection method.Korean Air developed its new UAV flight control software using Model-Based Design. Rong Z, Wenjie H, Wen T (2018) Applicability and tuning of linear active disturbance rejection control. National Defense Industry Press, Beijing, pp 280–281 Jingqing H (2009) Active disturbance rejection control technology. AIAA SciTech Forum and Exposition, pp 1364–1379. Appl Math Model (Mara): 709–722ĭeslich J, Flick P, Meckstroth CM (2021) Evaluating the effectiveness of compliant leading edge control surfaces on an oblique flying wing for directional control. Guerrero-Sanchez ME, Lozano R (2021) Nonlinear control strategies for a UAV carrying a load with swing attenuation. Rogalski T, Nowak D (2019) Control system for aircraft take-off and landing based on modified PID controllers. Wei S, Yanzhao Y (2020) Aerodynamic modeling and flight simulation of Tailseat UAV with flying wing layout. Beihang University Press, Beijing, pp 20–22 Zhenping F (2005) Flight dynamics of aircraft. Zhang T, Li Q, Zhang C (2018) Development trend of intelligent unmanned autonomous systems.
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Yi Y, Li Z (2019) Unmanned aerial vehicle and future combat. Nanjing University of Aeronautics and Astronautics, Nanjing, pp 68–93 Donghong Z (2018) Research on automatic landing technology of UAV with high aspect ratio.