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31 October 2006 Robust nonlinear dynamic inversion flight control design using structured singular value synthesis based on genetic algorithm
Sibin Ying, Jianliang Ai, Changhang Luo, Peng Wang
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Proceedings Volume 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation; 63584N (2006) https://doi.org/10.1117/12.718217
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China
Abstract
Non-linear Dynamic Inversion (NDI) is a technique for control law design, which is based on the feedback linearization and achieving desired dynamic response characteristics. NDI requires an ideal and precise model, however, there must be some errors due to the modeling error or actuator faults, therefore the control law designed by NDI has less robustness. Combining with structured singular value μ synthesis method, the system's robustness can be improved notably. The designed controller, which uses the structured singular value μ synthesis method, has high dimensions, and the dimensions must be reduced when we calculate it. This paper presents a new method for the design of robust flight control, which uses structured singular value μ synthesis based on genetic algorithm. The designed controller, which uses this method, can reduce the dimensions obviously compared with the normal method of structured singular value synthesis, so it is easier for application. The presented method is applied to robustness controller design of some super maneuverable fighter. The simulation results show that the dynamic inversion control law achieves a high level of performance in post-stall maneuver condition, and the whole control system has perfect robustness and anti-disturbance ability.
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Sibin Ying, Jianliang Ai, Changhang Luo, and Peng Wang "Robust nonlinear dynamic inversion flight control design using structured singular value synthesis based on genetic algorithm", Proc. SPIE 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation, 63584N (31 October 2006); https://doi.org/10.1117/12.718217
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KEYWORDS
Genetic algorithms
Control systems
Control systems design
Nonlinear control
Device simulation
Structural design
Complex systems
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