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This paper presents a novel control design strategy for the hypersonic vehicle using the elastic surrogate model. First, the parametric model is established for the rigid mode of the hypersonic vehicle based on the engineering estimation and panel methods. Then, the beam surrogate model is applied to identify the elastic mode of the hypersonic vehicle, and the complete parametric model including the rigid and elastic modes is obtained accordingly. Afterward, the control-relevant model is acquired based on the Morris sensitivity analysis method. Furthermore, the control system using the surrogate model is proposed for the hypersonic vehicle to suppress elastic disturbances and maintain system stability. Finally, an illustrative example of the hypersonic vehicle is provided to verify the effectiveness of the presented methods. [ABSTRACT FROM AUTHOR]

Waverider hypersonic vehicles have the characteristics of strong coupling between subsystems and the wide range flight envelope. Therefore, the control analysis and synthesis should be integrated into the early stage of vehicle design, the parameters in control system should be optimized as well as the parameters in aerodynamic, propulsion and structure systems in the vehicle design, and the software tool to facilitate the design process should be developed. Firstly, a series of parameters are used to describe the geometric, and a parameterized model of hypersonic vehicles is established. Then, the objective function is determined according to mission requirements, and then optimal parameter set will be obtained by searching variables in design space to satisfy the constraints. Then, the control relaxed specifications, such as controlability, stability, robustness and time-domain performances etc., are set as the optimization indexes, and the proposal on how to adjust parameters is feedbacked to optimization loop. A optimal vehicle configurations is obtained. Finally, the software, which is used to assist vehicle design, is able to carry out vehicle modeling, analyze static and dynamic characteristics, and provide various controller design templates automatically. [ABSTRACT FROM AUTHOR]

For the air-breathing hypersonic vehicles (AHSV) with a broad flight envelope, this paper proposes a new controller design method to ensure robust stability in the presence of external disturbances. The proposed method is based on the guardian maps theory and H ∞ Linear Parameter Varying (LPV) technique. In this paper, an LPV model of the AHSV is firstly established using the Jacobian linearization method. By incorporating the guardian maps theory and H ∞ technique, a set of controllers is designed such that the closed loop poles lie in the desired area. The major merit of the proposed method is that all controller parameters over the overall flight envelope can be automatically determined in the iterative courses that are started from an arbitrary initial point within the flight envelope. Finally, the proposed approach is demonstrated by an illustrative example. The results show that the designed controller is operated to stabilize the air-breathing hypersonic vehicle over a wide flight envelope, and to exhibit satisfactory tracking performance as well as strong robustness. [ABSTRACT FROM AUTHOR]

Guardian maps provide a concise and practical approach to parametric robustness analysis. However, non-convexity and nonlinearity of high dimensional guardian maps restrict the application. In this paper, a closed-loop performance-oriented approach to parametric robustness analysis is proposed. First, a sufficient condition for the existence of parametric stable region satisfying the closed-loop performance is presented. To further identify the maximum stable region, a robustness criterion is provided, leading to a numerical approach for parametric stability margin. The superiority of the proposed method lies in the applicability to robust performance analysis with nonlinear high-dimensional parameters. Applications are discussed with emphasis on the flight control of hypersonic vehicles, including robust control design and robust stability analysis. Results are of significant that no prior knowledge on controller tuning is required, and parametric stability margin can be obtained automatically regardless of the dimension of parameter space. [ABSTRACT FROM AUTHOR]