Hypersonic Vehicle System Research Articles

Backstepping control of hypersonic vehicles under input and output constraints with model uncertainties and disturbances

In this paper, considering the physical restriction of hypersonic vehicle systems in a practical flight environment, the altitude tracking problem is studied with input magnitude, input rate, output constraints, system parameter uncertainties and disturbances, which expands the traditional considerations of control methods in the hypersonic vehicle field. The hyperbolic tangent function is employed to address the system input constraints. Furthermore, the incorporation of barrier Lyapunov function serves to ensure that the system output is limited in the prescribed limitations. In particular, two extended state observers are integrated to eliminate errors from model uncertainties and disturbances. Based on the effective combination of these techniques and auxiliary variable designs, a novel backstepping controller is proposed to simultaneously handle problems of input and output constraints, model uncertainties and disturbances. The closed-loop system stability is demonstrated using the Lyapunov theory. Simulation results show the effectiveness and superiority of the proposed controller compared with the traditional backstepping controller.

Flight parameter prediction for high-dynamic Hypersonic vehicle system based on pre-training machine learning model

Flight parameter prediction for high-dynamic Hypersonic vehicle system based on pre-training machine learning model

Adaptive backstepping fault-tolerant control for hypersonic aircraft with unknown control direction under actuator and sensor faults

Abstract In this paper, an adaptive backstepping controller of hypersonic flight vehicle (HFV) system is investigated in the presence of unknown actuator and sensor faults, unknown control direction and varying external disturbance, which expands traditional fault-tolerant control (FTC) approaches in HFV field. The control-oriented model is established with reasonable and comprehensive analysis of various fault types. Compared with the previous FTC research on HFV system, the time-varying and fixed fault types are simultaneously designed for actuator and sensors, and the control direction is unknown, which can more accurately simulate the real fault situations in the hypersonic flight environment. To avoid singularity problems caused by the unknown control direction, the Nussbaum gain function technique is adopted in the control algorithm, which is also capable of overcoming the influence of unknown time-varying fault parameters. The boundness and stability of system under the designed control scheme are theoretically verified. Finally, numerical simulation results demonstrate the effectiveness and superiority of the proposed control strategy.

Adaptive fault‐tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

AbstractThis paper proposes an adaptive fault‐tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time‐varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time‐varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time‐varying state constraint function (TVSCF). A unified controller is designed to handle the time‐varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free‐constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum‐type function is designed to compensate for those time‐varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed‐loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault‐tolerant control scheme.

Nonlinearly Parametrized Modeling and Adaptive Control for a Generic Hypersonic Vehicle

This paper constructs a nonlinearly parametrized hypersonic cruise vehicle model on the basis of the existing on-orbit flight data using a curve-fitting technique. The hypersonic cruise vehicle system is separated into two interconnected subsystem: an attitude subsystem with rotational dynamics and a velocity subsystem with engine dynamics. The continuous adaptive controllers are designed for two subsystems using a novel function bounding technique and appropriate coordinate transformations, respectively, which ensure the global boundedness of all signals and achieve the non-zero equilibrium point regulation of nonlinearly parametrized hypersonic vehicle systems. One of the implications of this result is that growing nonlinearities in the uncertain model of the hypersonic vehicle system may be allowed for global stabilization. A simulation result verifies the effectiveness of the proposed adaptive control scheme.

A novel funnel control mechanism for hypersonic flight vehicles under input constraints

This article proposes a novel adaptive neural network funnel control scheme based on auxiliary system, which is used to solve the problem that the conventional funnel control strategies have difficulty in solving the control singularity problem caused by transiently increasing tracking errors under input constraints. To begin, the longitudinal motion model of hypersonic flight vehicle is split into a velocity subsystem and an altitude subsystem, with the velocity subsystem being controlled by a proportional integral funnel controller and the altitude subsystem being controlled by an adaptive neural network funnel controller. An adaptive neural network funnel controller is designed for altitude subsystem, which is turned into a pure feedback form. Next, the auxiliary system is used to compensate the control law and tracking error, the neural network is used to estimate the system uncertainty, and the funnel control is used to constrain the tracking error to meet the steady-state and dynamic requirements of hypersonic flight vehicle system. The stability analysis proves the stability of funnel controller. The robustness of our newly proposed method is demonstrated by the simulation results.

Review of Research Methods for Hypersonic Vehicle Reentry Trajectory Planning

Hypersonic vehicle has many advantages, such as wide range of maneuver, strong penetration ability, high strike accuracy, and so on. Reentry trajectory planning is one of the key technologies to support hypersonic vehicle systems. It is necessary to plan feasible or optimal trajectory under the process constraints such as heat flux, dynamic pressure, overload, and terminal constraints such as altitude and velocity. At present, traditional methods are difficult to meet the task requirements of trajectory planning and online trajectory generation under complex conditions with multiple constraints. As an artificial intelligence method, reinforcement learning has strong robustness and the characteristics of "offline training and online deployment", which can make up for the shortcomings of traditional methods and show great potential in trajectory planning. This paper introduces the current research status of traditional trajectory planning methods and reinforcement learning methods, and proposes that the reentry trajectory planning methods will be intelligent in the future.

Integrated design of adaptive fault-tolerant control for non-minimum phase hypersonic flight vehicle system with input saturation and state constraints

In this paper, for the six-degree-of-freedom (six-DOF) model of hypersonic flight vehicle (HFV) subject to actuator faults, state constraints, parametric uncertainties, and external disturbances, an adaptive fault tolerant control (FTC) scheme is proposed based on barrier Lyapunov functions (BLFs). The study is begun with a series of control-oriented manipulations: at first, due to the high complexity of the six-DOF model, the corresponding simplified model is proposed under reasonable assumptions; then, through the stability analysis of the internal dynamics, we can conclude that the vehicle model is a non-minimum phase system, namely, having unacceptable zero-dynamics. In order to solve the non-minimum phase problem, the elevator-to-lift coupling term is regarded as uncertainty of the model. Subsequently, in consideration of the insufficient control torque caused by the fault of the rudder or elevators, an adaptive fault-tolerant controller is designed based on BLFs, backstepping method, and Nussbaum gains. In the control law, the uncertain parameters are replaced by their estimates updated by adaptive laws. And the angle of attack and the roll angle of the aircraft are constrained in the preset range. Additionally, the convergence of the proposed FTC algorithm and the boundedness of all the signals of the closed system is proved by Lyapunov stability theory. At last, the numerical simulation results of the six-DOF model are carried out to manifest the effective tracking performance of the proposed FTC scheme.

Global adaptive neural backstepping control of a flexible hypersonic vehicle with disturbance estimation

PurposeThis paper aims to discuss the precise altitude and velocity tracking control of a hypersonic vehicle, a global adaptive neural backstepping controller was studied based on a disturbance observer (DOB).Design/methodology/approachThe DOB combined with a radial basis function (RBF) neural network (NN) was used to estimate the disturbance terms that are generated by the flexible modes of the hypersonic vehicle system. A global adaptive neural method was introduced to approximate the unknown system dynamics, with robust control terms pulling the system transient states back into the neural approximation domain externally.FindingsThe globally uniformly ultimately bounded for all signals of a closed-loop system can be guaranteed by the proposed control algorithm. Additionally, the command filtered backstepping methods can avoid the explosion of the complexity problem caused by the backstepping design process. In addition, the effectiveness of the proposed controller can be verified by the simulation used in this study.Research limitations/implicationsNormally lateral dynamics issue should be discussed in the process of control system designed, the lateral dynamics are not included in the nonlinear dynamic model of hypersonic vehicle used in this paper, merely the longitudinal flight dynamics are discussed in this paper.Originality/valueThe flexible states in rigid modes are considered as the disturbance of the system, which is estimated by structuring DOB with NN approximations. The compensating tracking error and prediction error are used in the update law of RBF NN weight. The differential explosions complexity derived from the backstepping procedure is dealt with by using command filters.

Learning-based adaptive fault tolerant control for hypersonic flight vehicles with abrupt actuator faults and finite time prescribed tracking performance

This paper addresses the finite time prescribed performance control problem for hypersonic flight vehicle systems with abrupt actuator faults and time-varying uncertainties. The considered actuator faults contains abrupt gain faults and saltatorial bias faults, and the unknown discontinuous variations of the fault parameters are permitted. In virtue of the finite time performance functions and error transformation, the predefined tracking performance including the convergence time, the tracking error and the overshoot for the velocity and altitude can be ensured. By adaptively estimating the lower bonds of the gain faults and the upper bounds of the bias faults, the unwanted effects of the abruptly faulty actuators can be circumvented. Meanwhile, for the purpose of compensating the unknown nonlinearities, the learning-based control strategy has been employed. Finally, a number of simulation results on the hypersonic flight vehicles are conducted to demonstrate the validity of the proposed approach.

Fault Detection for A Class of Closed-loop Hypersonic Vehicle System via Hypothesis Test Method

This paper studies the fault detection problem for a class of hypersonic vehicle with actuator faults, disturbances and random noises. To handle the unknown disturbances, an unknown input Kalman filter (UIKF) is presented to estimate the unknown system states and disturbances, simultaneously. Considering that the closed-loop structure brings the robustness to the hypersonic vehicle, which could cover some faults, the Total Measurable Fault Information Residual (ToMFIR) is employed as the fault detection residual. Moreover, to deal with the random noises, the hypothesis testing method is utilized to obtain the thresholds under some fault detection performances (false alarm rate and missing alarm rate). The fault detectability condition is also derived. Finally, the simulations verify the effectiveness of the proposed fault detection method.

Synchronous Fault-Tolerant Near-Optimal Control for Discrete-Time Nonlinear PE Game.

In this article, the synchronous fault-tolerant near-optimal control strategy design problem is studied for a class of discrete-time nonlinear pursuit-evasion (PE) games. In the studied PE game, the input saturation phenomenon and possible actuator fault are simultaneously taken into consideration. To accelerate the estimation speed, a novel nonlinear fault estimator is designed by introducing a nonlinear function. Then, for the purpose of obtaining the synchronous control strategy for the discrete-time PE games, an approximate Hamilton-Jacobi-Isaacs (HJI) equation is established, which is seldom utilized for the discrete-time approximate dynamic programming in most existing results. It should be noticed that the synchronous control strategy designed based on the approximate HJI equation can be convergent very fast because of its quasi-Newton's iteration form. Furthermore, the sufficient condition is established to guarantee that the studied system is uniformly ultimately bounded. Finally, a numerical simulation of the hypersonic vehicle system is carried out to validate the proposed methodology.

Adaptive fault tolerant control for hypersonic flight vehicle system with state constraints

In this paper, an adaptive fault tolerant control (FTC) scheme based on barrier Lyapunov functions (BLFs) for the hypersonic flight vehicle (HFV) with state constraints is proposed. Complexities of the aerodynamical uncertainties, external disturbances and flexible dynamics are taken into account in the controller design process. The paper deals with the MIMO system properly so that the backstepping technique based on BLFs can be successfully used for the issue of state constraints without neglecting the coupling of HFV system. To aim at the unknown faults of the elevators, an adaptive FTC mechanism is introduced to the BLFs-based controller, which increases the reliability of the system. Finally, simulations are conducted to verify the validity of the designed controller.

Disturbance Rejection Control Based on Linear Quadratic for Nonminimum-phase Hypersonic Flight Vehicle System

This paper proposed a disturbance rejection control method based on linear quadratic (LQ) for nonminimum-phase discrete-time systems with unmatched signals. By introducing a new cost function that considers the influences of disturbance on the input signal, we apply the novel control method to hypersonic flight vehicle (HFV) system to solve the problem of turbulence compensation. A two-component control input is generated through systematic derivation of finite-time LQ optimal control law, improving the stability, output regulation capability, and robustness of the HFV system. Comparison analysis under different control schemes in simulation study shows the effectiveness of the proposed method.

Fault diagnosis and accommodation with flight control applications

ABSTRACTThis paper reviews some main results and process concerning with fault diagnosis and accommodation with flight control applications. The fault detection and diagnosis including the quantitative and qualitative methods and the fault-tolerant control including passive and active schemes are introduced, respectively. The control designs and developments of the fault diagnosis and accommodation for continuous-time systems and discrete-time systems, the fault diagnosis and fault-tolerant control for switched systems and interconnected systems as well as the applied flight control research including hypersonic vehicle, spacecraft and helicopter systems are summarised.

Neural network based integral sliding mode optimal flight control of near space hypersonic vehicle

In this paper, based on the integral sliding mode method and adaptive dynamic programming (ADP) algorithm, a robust optimal tracking control scheme is presented for near space hypersonic vehicle (NSHV) system in the presence of unknown modeling error, external disturbance, and input saturation. Firstly, combining neural network, auxiliary system and integral sliding mode methods, an adaptive integral sliding mode control (AISMC) law is designed to guarantee system trajectories tend to a defined integral sliding surface and the effects of modeling uncertainty, external disturbance, and control input saturation are eliminated. Then, the robust optimal tracking control problem of original system is converted into the optimal control problem of a nominal system, and an ADP method with single critic network is utilized to acquire the corresponding optimal controller. Furthermore, Lyapunov analysis method shows that the overall control input which contains AISMC law and optimal controller can ensure all the signals in closed-loop system are stable in the sense of uniform ultimate boundedness (UUB). Finally, simulation results about attitude flight control of NSHV are given to verify the effectiveness of the proposed control scheme.

Fuzzy-approximation-based prescribed performance control of air-breathing hypersonic vehicles with input constraints.

In this article, aiming at the longitudinal dynamics model of air-breathing hypersonic vehicles, a fuzzy-approximation-based prescribed performance control scheme with input constraints is proposed. First, this article presents a novel prescribed performance function, which does not depend on the sign of initial tracking error. And combining prescribed performance control method with backstepping control, the control scheme can ensure that system can converge at a prescribed rate of convergence, overshoot, and steady-state error. In order to solve the problem that backstepping control method needs to be differentiated multiple times, fuzzy approximators are used to estimate the unknown functions, and norm estimation approach is used to simplify the computation of fuzzy approximator. Aiming at the problem of input saturation of actuator in subsystem of air-breathing hypersonic vehicle, the new auxiliary system is designed to ensure the stability and robustness of air-breathing hypersonic vehicle system under input constraints. Finally, the effectiveness of the proposed control strategy is verified by simulation analysis.

Passive Fault-tolerant Control Based on Weighted LPV Tube-MPC for Air-breathing Hypersonic Vehicles

This paper proposes a novel passive fault-tolerant control method using weighted tube-based model predictive control (Tube-MPC) via polytopic linear parameter varying (LPV) for air-breathing hypersonic vehicles. Firstly, the longitudinal LPV model of the vehicle is established by the Jacobi linearization and tensor-product (T-P). The random drift fault or loss of efficiency fault over the elevator deflection is transformed equivalently into the additional item as bounded disturbance. Based on invariant set theory, a weighted Tube-MPC control method is proposed. In traditional Tube-MPC controller design, the worst case of the fault is generally considered. In order to balance control performance and robustness of the control system, this paper introduces a weighted strategy, where the weighted factor α is used to change the robust positive invariant (RPI) set for incomplete fault set. The robustness of the system is sacrificed, so that the invariant set can be reduced to expand the domain of the nominal control input. In this way, the control performance of the nominal system can be improved. In the actual flight, the states of the hypersonic vehicle system cannot be measured completely, and therefore a polytopic Luenberger state observer is developed to estimate the unmeasured states. The control errors and estimate errors are limited by two incomplete disturbance minimum RPI (idmRPI) sets. Finally, simulations verify the fault-tolerant ability and tradeoff regulating ability of the designed control system.

Mapped Chebyshev pseudospectral methods for optimal trajectory planning of differentially flat hypersonic vehicle systems

This paper presents a novel trajectory planning algorithm for hypersonic glide vehicles based on differentially flatness theory and mapped Chebyshev pseudospectral method (MCPM). Firstly, the flatness property of a hypersonic glide vehicle dynamics system is extended explicitly by introducing a pseudo control input along the opposite direction of aerodynamics drag. In this way, all the states and controls of the system can be represented by flat outputs and their derivatives, and the trajectory planning problem is formulated into the flat output space with differential constraints entirely eliminated. Secondly, the optimization problem in the flat output space is converted into a nonlinear programming one via the mapped Chebyshev pseudospectral method. The MCPM employs the conformal mapping principle to discretize the flat outputs at the time interval, in terms of which, the closely clustered Chebyshev points near the boundary are stretched and the ill-conditions of the differential matrix is improved. The Barycentric Lagrange interpolation algorithm is then utilized to interpolate the flat output functions, which is seized of better approximation properties than polynomial interpolation. Finally, the transformed nonlinear programming problem are solved by sequence quadratic program technique. The states and controls are then generated by the expressions of the flatness outputs. At the end of this paper, numerical simulations are performed to evaluate the proposed approaches, and comparisons are made with traditional methods. Simulation results demonstrate that the proposed differentially flatness based mapped Chebyshev pseudospectral method possessed better computing efficiency than traditional ones without losing the merits of high precision.

Decentralized static output feedback sliding mode control for interconnected descriptor systems via linear sliding variable

This paper investigates a linear sliding variable-based decentralized static output feedback sliding mode controller design problem of interconnected descriptor systems. A generalized regular form for interconnected descriptor systems is introduced. Based on the generalized regular form, a linear matrix inequality-based method is given to solve the designing matrix in the linear sliding variable and a decentralized static output feedback sliding mode controller is synthesized to stabilize the interconnected descriptor systems. It is shown that the proposed static output feedback sliding mode control method can still stabilize the interconnected descriptor systems even when unknown matched disturbances exist. Finally, a simulation result on the hypersonic vehicle system is given to illustrate the validity of the proposed method.