Invariant Tensor Modeling and Functional Matrix Coding of Flight Dynamics for Nonlinear Aircraft Control

Flight trajectory consistence is an important factor influencing mission performance and safety. However, the lack of in-situ flight dynamics with high fidelity remains a challenge to enhance stability and controllability for aircraft maneuver in space, because modeling and coding of predictive system response in control synthesis is difficult to be mathematically formulated and computationally implemented. Here we generalize the invariant tensor modeling of flight dynamics so that its functional matrix coding is adapted to the multivariable nonlinear control of aircraft with augmented stability and controllability; and we verify that the nonlinear functional parameters in control synthesis with unobservable external forces and moments can improve the consistence of flight trajectory. Results demonstrate that the planned flight trajectory can be consistently fulfilled using the nonlinear control synthesized through tensor modeling and matrix coding. In conclusion, invariant tensor modeling facilitates the functional matrix coding of flight dynamics with six degrees of freedom, which can be applied to build the feedback through dimensional analysis for augmented stability and controllability, such that collaborative optimization of nonlinear functional parameters establishes the multivariable nonlinear control to improve the consistence of flight trajectory for sustained performance and continuing safety.