Modeling and nonlinear control for air-breathing hypersonic vehicle with variable geometry inlet

Dou, Lihua; Su, Peihua; Ding, Zhengtao

doi:10.1016/j.ast.2017.04.024

Cited by 35 publications

(17 citation statements)

References 38 publications

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“…Assume that the engine automatically changes from one cycle to the next. The specific impulse is set as functions of the Mach number (denoted by Ma ):

I_{s} = ({, \begin{array}{l} 3520 - 220 italicMa 0 \leq italicMa < 3 \\ 2860 - 260 ((), italicMa - 3) 3 \leq italicMa < 6 \\ 2080 - 300 ((), italicMa - 6) 6 \leq italicMa < 12 \\ 280 12 \leq italicMa . \end{array})

…”

Section: Mathematical Modelsmentioning

confidence: 99%

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Ascent trajectory optimization for air‐breathing vehicles in consideration of launch window

Hong-yu

Wang

Cui

2019

Optim Control Appl Methods

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Summary This paper studies the optimal ascent trajectory for a one‐stage‐to‐orbit, air‐breathing vehicle. This kind of vehicle allows endoatmospheric lateral maneuver and thus can extend the launch window. To obtain the optimal orbit‐insertion trajectory in consideration of launch time, a novel optimization model is proposed by designing longitudinal and lateral profiles separately. The longitudinal flight aims to meet the orbital shape that contains the eccentricity and the angular momentum, which are transformed to boundary constrains in altitude, path angle, and velocity. For lateral motion, the orbit inclination and right ascension of ascending node are designed to vary simultaneously as the range. By designing an altitude profile, the terminal altitude and path angle are naturally met and removed from the constraints and accurate orbit insertion is realized by searching the total range and the initial azimuth. Then, the original problem is converted to a parameter optimization problem and solved by a hybrid optimization algorithm, in which the solution is first searched by a particle swarm optimization method and then refined by a modified golden section method. Simulation tests the proposed method with various scenarios. Compared to traditional launch vehicles, a launch window over 1.5 hours is derived without consuming the propellant in the upper stage.

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“…Assume that the engine automatically changes from one cycle to the next. The specific impulse is set as functions of the Mach number (denoted by Ma ):

I_{s} = ({, \begin{array}{l} 3520 - 220 italicMa 0 \leq italicMa < 3 \\ 2860 - 260 ((), italicMa - 3) 3 \leq italicMa < 6 \\ 2080 - 300 ((), italicMa - 6) 6 \leq italicMa < 12 \\ 280 12 \leq italicMa . \end{array})

…”

Section: Mathematical Modelsmentioning

confidence: 99%

“…Assume that the engine automatically changes from one cycle to the next. The specific impulse is set as functions of the Mach number (denoted by Ma) 13,31,32 :…”

Section: Models Of the Air-breathing Vehiclementioning

confidence: 99%

Ascent trajectory optimization for air‐breathing vehicles in consideration of launch window

Hong-yu

Wang

Cui

2019

Optim Control Appl Methods

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“…Furthermore, the grades of secondary membership functions in T2 fuzzy sets can be simply set to 1 and the so-called interval T2-FLSs (IT2-FLSs) are developed [31] which owes the benefits of lower computational expense when compared with general T2-FLSs. Recently, based on the universal approximation property of the IT2-FLSs, several intervals T2 fuzzy adaptive control approaches were developed in the flight control [33,34], tracking control of surface vessels [35], and power system control [36]. A direct adaptive T2-FL controller was designed for HVs where IT2-FLSs were used to approximate the dynamic inversion control signals in [33].…”

Section: Introductionmentioning

confidence: 99%

“…A direct adaptive T2-FL controller was designed for HVs where IT2-FLSs were used to approximate the dynamic inversion control signals in [33]. Considered the uncertain changes induced by variable geometry inlet, in [34], an adaptive IT2 fuzzy sliding mode controller was designed for HVs and IT2-FLSs were adopted to approximate non-linear parts including the uncertain changes. The results in the above literatures show that in the presence of large model uncertainties, the IT2 fuzzy adaptive control approach performs better than the T1 counterpart.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based robust adaptive T2 fuzzy tracking control for flexible air‐breathing hypersonic vehicles

Liu

2018

IET Control Theory & Applications

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“…In this paper, the estimated value of the elongation distance is presented by curve fitted approximation [43]. The expression of fitting elongation distancel is shown in (7).…”

Section: Basic Principle Of Ahv-vgi With Translating Cowlmentioning

confidence: 99%

Fuzzy disturbance observer‐based dynamic surface control for air‐breathing hypersonic vehicle with variable geometry inlets

Dou

Zong

et al. 2018

IET Control Theory & Applications

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Abstract:For an air-breathing hypersonic vehicle with a variable geometry inlet (AHV-VGI), a movable translating cowl is used to track the shock on lip conditions to capture enough air mass flow, which can extend the velocity range and be favorable to the acceleration and maneuvering flight. We firstly establish longitudinal dynamics for AHV-VGI, and consider the lumped disturbances which include the unknown external disturbance, the parameter uncertainties and the uncertainty parts introduced by translating cowl. Then, the dynamic surface control (DSC) strategy based on fuzzy disturbance observer (FDO) is proposed for AHV-VGI control. The control process for AHV-VGI is divided into two subsystems. For each subsystem, a sliding mode controller is designed, and FDOs are adopt to compensate the lumped disturbances, which can render the disturbance estimate errors convergent. Numerical simulations are presented to illustrate the effectiveness of the proposed method and the advantages of translating cowl. IntroductionAs a reliable and more cost-efficient way to access space, airbreathing hypersonic vehicle (AHV) has been investigated by many researchers in recent decades [1]. This type of vehicle has a unique design, incorporating a supersonic combustion scramjet engine located beneath the fuselage, which enable it quick response and global reach [2]. In practice, the AHV always fly within a wide flight envelope (range of flight conditions). However, for the AHV with fixed geometry inlet(AHV-FGI), once it is running at a low Mach number, the shockwave would deviate away from the scramjet lip. This leads to the scramjet engine could not get sufficient air stream, so that the thrust would be insufficient. In order to solve the above issue, AHV with variable-geometry inlet(AHV-VGI) are popularly studied. For example, NASA investigates a rotary lip VGI for the X-43A hypersonic aircraft [3]. The Space and Astronautical Science institution of Japan developed a variable geometry axisymmetric inlet for the ATREX engine [4]. Besides, the Russian scholar Kuranov investigated the Magneto Hydrodynamic controlled inlet [5].In the past decades, lots of efforts have also been put into flight control of AHV. Feedback linearization is a powerful tool to deal with the intrinsic nonlinear system [6]. The robust control of AHV is studied to improves the tracking control performance effectively [7]. To overcome the problem of system uncertainty, fuzzy logic system [8] and neural network [9] are employed due to their powerful ability of approximation for the smooth nonlinearities. Recently, transient performance-based control design [10][11] has become an important method for the research of uncertain nonlinear systems. Ref.[12] proposed a novel estimation-free prescribed performance non-affine control strategy for AHV to guarantee tracking error is limited to a predefined arbitrarily small residual set. Beside, Various techniques have been applied to hypersonic vehicles to deal with parametric uncertainties or bounded uncertainties and ...

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Modeling and nonlinear control for air-breathing hypersonic vehicle with variable geometry inlet

Cited by 35 publications

References 38 publications

Ascent trajectory optimization for air‐breathing vehicles in consideration of launch window

Ascent trajectory optimization for air‐breathing vehicles in consideration of launch window

Observer‐based robust adaptive T2 fuzzy tracking control for flexible air‐breathing hypersonic vehicles

Fuzzy disturbance observer‐based dynamic surface control for air‐breathing hypersonic vehicle with variable geometry inlets

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