Robust Controller Design Of Hypersonic Vehicle Based On QFT

Hypersonic vehicle has important strategic significance and a high application. The tremendous changes of the aerodynamic characteristics caused by special and complicated environment, and the coupling among impetus/structure/pneumatic caused in the integrative design, make it hard to establish reliable flight parameter recorder. So it is significant to study the hypersonic vehicle with parametric uncertainty. Because of the seriouse uncertainty of the parameters, this article mainly talks about the robust controller design using quantitative feedback theory of the hypersonic vehicle.The quantitative feedback theory (QFT) is a method of robust control design, which has gains more popularity in recent years. It also has high value of engineering practicability. Firstly, the QFT’s basic knowledge is introduced, and the performanee in t-domain and and ω-domain plant with uncertainty and unknown output disturbance are analyzed. Then, some important problems, which are solved in the QFT design proeess, are analyzed and studied, for example, controller strueture, plant templates, performance target bounds, loop-shaping, pre-filter designing, and so on. So, design proeess for LTI/SISO systems and cautions are summarized. And basic managing methods are put forward for LTI/MIMO systems, such as non-least phase/instability systems, and uncertain time-varying/nonlinear systems.Aim at the control problem during the hypersonic vehicle’s flight, this article views the influence which comes from variable working state, as the extension of the uncertainty model. Then this article uses the quantitative feedback theory (QFT) to design a robust controller. By converting the time-domain indices in the flight control system into frequency domain indices it creates intersection bounds in the Nichols chart. And by using the loop shaping technology to design the controller and the prefilter, it makes closed-loop in frequency domain meet the performance index. It restrains the output disturbance and makes the systems have vell robust performance, when the parameters of the system model have variable changes. This method has preferable practical value.