No abstract

A discrete reconfigurable back-stepping controller is proposed to resolve the attitude command tracking problem of hypersonic flight vehicle in reentry mode. The hypersonic flight vehicle dynamic equations are transformed into discrete form based on Euler numerical integration method. Discrete control command is designed via discrete back-stepping. Control allocation strategy is introduced to deal with the resource distributing problem of reaction control system and aero-surfaces. In computer simulation environment, the vehicle tracks command signals precisely and quickly.

Because a light field camera first takes an image and then refocuses it, we propose a scene distance measurement method based on light field imaging spatial refocusing principles, which was used to generate sequences of refocused images from raw spatial scene images taken by a Lytro1 light field camera. We selected the window of the object whose scene distance needed to be measured, used image-resolution evaluation functions to choose one of the clearest images among the refocused image sequences, and employed Gaussian formula to deduce the scene distance measurement formula. Finally, we used the scene distance measurement method to measure an object on the scene and theoretically analyzed its measurement range and accuracy. The experimental results showed that this scene distance measurement method provides the scene distance information.

The missile-based redundant SINS (strap-down inertial navigation system) output the measurement data by using pulse quantization. Pulse quantization can disorganize the errors in the original measurement signal, cause an instantaneous drift of 50 degree/hour, and thus brings about great difficulty to the process of fault diagnosis. Focusing on the problem that the pulse quantization results in difficulty to the fault diagnosis of the redundant SINS, this paper proposes a method that using a low pass filter reduces the quantization noise. Based on GLT (generalized likelihood test) method, one of the methods used for fault diagnosis of the redundant SINS and combined with a low pass filter, this paper studies the effects before and after the fault diagnosis comparatively and draws a conclusion that a low pass filter is helpful for improving the effect of quantitative fault diagnosis. The result of the simulation experiment shows that the effect of the fault diagnosis after improving is close to that before using pulse quantization, and that the effect can detect the order of 5 degree / hour accurately.

Inspired by the exceptional flight ability of birds and insects, a bio-inspired neural adaptive flight control structure of a small unmanned aerial vehicle was presented. Eight pressure sensors were elaborately installed in the leading-edge area of the forward wing. A back propagation neural network was trained to predict the aerodynamic moment based on pressure measurements. The network model was trained, validated, and tested. An adaptive controller was designed based on a radial basis function neural network. The new adaptive laws guaranteed the boundedness of the adaptive parameters. The closed-loop stability was analyzed via Lyapunov theory. The simulation results demonstrated the robustness of the bio-inspired flight control system when subjected to measurement noise, parametric uncertainties, and external disturbance.