Model Of Hypersonic Flight Vehicle Research Articles

Integral reinforcement learning–based adaptive fuzzy fault tolerant control of hypersonic flight vehicle

The fault tolerant control (FTC) of hypersonic flight vehicle (HFV) with actuator fault is proposed in this paper. The fault model considered in this paper is a general model which HFV may encounter in practice. For designing the FTC, the nonlinear model of HFV is represented by T-S fuzzy models, and policy iteration (PI) strategy is utilized to solve the design problem of T-S controller for the built T-S model of HFV without actuator fault. Then, based on the normal T-S controller, an adaptive fuzzy FTC controller is proposed, in which the feedback gain matrices can improve themselves according to the special fault. The stability of the proposed adaptive fuzzy FTC is proved by Lyapunov theory, and an integral reinforcement learning (IRL)–based solving algorithm is proposed. Simulations on three different kinds of actuator faults are proposed, and the simulation results show that, under three different faults, the designed adaptive FTC can ensure the reliable flight of HFV.

Unmeasurable flexible dynamics monitoring and tracking controller design for guidance and control system of hypersonic flight vehicle

The guidance and control system (GCS) is an important and indispensable component of hypersonic flight vehicle (HFV), and it can be viewed as a special cyber–physical system (CPS). However, the monitoring of the HFV dynamics is difficult since the inertial navigation equipment can only provides the information of acceleration and angular rate. In this case, the flexible states of HFV are difficult to be measured. This paper proposes a sliding mode observer (SMO) based GCS design method for HFV. With considering the measurement difficulties, the flexible states of HFV are assumed to be unmeasurable. Then a SMO is designed to estimated them. Combined with the actual flight environment of HFV, the measuring devices are assumed to be suffering from disturbance, then the SMO should not only guarantee the estimation error stable, but also reduce the influence of external disturbances. What is worse, the input of HFV is suffering from input delay, which brings more difficulties to the controller design. By state transformation,input delay model of HFV is transformed into a delay free model,then a SMO based robust controller is proposed for HFV based on the stable inversion controller design strategy. By the proposed SMO based controller, the GCS can be constructed for HFV. Numeral simulation are carried on HFV, and simulation results show shat, the designed SMO can realize the monitoring of flexible states of HFV and the designed GCS can get a good tracking performance.

Adaptive Performance-Constrained Synchronization Control for Hypersonic Flight Vehicle Swarms: A Novel Finite-Time Convergence Protocol Methodology

This paper proposes a novel neural adaptive performance-constrained synchronization tracking control algorithm for multiple hypersonic flight vehicles (HFVs), which are subject to actuator faults and full-state constraints. The proposed method is based on advanced Lyapunov finite-time stability theory and a sophisticated backstepping design scheme. The longitudinal model of HFV is converted into velocity and altitude subsystems through functional decomposition. Our method presents three significant contributions over the existing state-of-the-art approaches: (a) ensuring finite-time convergence of HFVs systems by guaranteeing that the setting time is lower bounded by a positive constant that is related to the initial states; (b) utilizing a tan-type Barrier Lyapunov function (BLF) to ensure that the synchronization tracking errors of velocity, altitude, flight path angle, angle of attack, and pitch angle rate are maintained within certain performance bounds; and (c) designing a neural adaptive control algorithm and adaptive parameter laws by combining the backstepping design technique and radial basis function neural networks (RBFNNs) to handle unknown actuator faults and modeling uncertainties. Finally, comparative simulations are conducted to validate the efficacy of the proposed scheme.

Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis

Hypersonic flight vehicle (HFV) with long term exposure to poor operating environments will inevitably experience performance degradation and potential failures. Currently, data-driven approaches have been commonly used for fault diagnosis. However, it is a challenge to obtain reliable and adequate data to identify HFV faults. To cope with this issue, this paper put forward a digital twin-assisted multiscale residual-self-attention feature fusion network (MRFFN) for hypersonic flight vehicle fault diagnosis. Firstly, a mathematical simulation is performed to establish the DT model of HFV. Then, the constructed DT model is employed for simulating multiple fault states of HFV to generate an approximation to the real system state data. Finally, a novel MRFFN is designed for training and validation utilizing the data derived from the DT model. The comparison performance demonstrates the MRFFN is superior to other intelligence methods in its ability to accurately identify hypersonic flight vehicle faults.

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.

Constrained Integrated Guidance and Control Scheme for Strap-Down Hypersonic Flight Vehicles with Partial Measurement and Unmatched Uncertainties

This paper investigates the issue of integrated guidance and control (IGC) design for strap-down hypersonic flight vehicles with partial measurement information and unmatched uncertainties. A constrained IGC scheme is proposed by combining the barrier Lyapunov function-based backstepping methodology and the specific output-based finite-time disturbance observer. Different from the existing methods, which require the state information and matched disturbances, the main features of the presented approach is capable of addressing the partial measurement knowledge and unmatched uncertainties simultaneously. The IGC model of hypersonic flight vehicles is first formulated, and based on that, the specific output-based finite-time disturbance observer (OFTDO) is proposed to achieve the finite-time estimation of the unmatched uncertainties through the output. Then, the constrained IGC strategy is constructed via the backstepping technique. The stability of the closed-loop system including the estimation and tracking errors dynamics is analyzed in detail. The effectiveness of the proposed method is verified by numerical simulations and Monte-Carlo tests.

Hybrid Adaptive Dynamic Inverse Compensation for Hypersonic Vehicles with Inertia Uncertainty and Disturbance

This paper studies an intelligent hybrid compensation scheme for the uncertain parameter and disturbance of hypersonic flight vehicles (HFV). For the longitudinal model of HFV with modeling errors, a nominal nonlinear dynamic inverse (NDI) controller ensures that the system output can accurately track the reference command. In the presence of rotational inertia uncertainty, a multi-learning law adaptive NDI controller is proposed to directly compensate for its impact on tracking performance, making the system robust to the uncertainty and reducing high maneuvering attitude angles and velocities vibration. Then, an improved adaptive NDI controller with a sliding mode disturbance observer is designed to actively compensate for the elastic mode disturbance, and continuously ensure the system’s anti-disturbance flight quality. Ultimately, this active–passive hybrid control scheme compensates for both high maneuvering inertia uncertainty and global disturbance. The Lyapunov functions prove the system’s stability, and the semi-physical simulation platform verifies the effectiveness of the method.

Sliding Mode Observer-Based Stuck Fault and Partial Loss-of-Effectiveness (PLOE) Fault Detection of Hypersonic Flight Vehicle

In order to improve the safety and reliability of the hypersonic flight vehicle, a sliding mode observer-based fault detection scheme is applied in this paper to handle the actuator fault detection issue, including stuck fault detection and PLOE fault detection. A dynamic linear model with uncertainty is first derived from the original nonlinear hypersonic flight vehicle model by using Taylor’s linearization approach at the equilibrium point. Secondly, the actuator fault model, reflecting stuck faults and PLOE faults, is constructed. Then, a sliding mode-based fault detection observer, considering system decomposition, is developed based on the linearized hypersonic flight vehicle model. At last, the designed sliding mode observer is applied to the original nonlinear hypersonic flight vehicle for single-input, single-style actuator fault detection. The simulation results show that stuck faults and big proportion PLOE faults can be timely and accurately detected at the fault time, and the stuck actuator fault from input 3 can cause a deadly impact to the hypersonic flight vehicle, which deserves much more attention than the actuator faults from the other three inputs. Meanwhile, the detection of a small proportion of PLOE faults encounters some difficulties and needs special attention and further investigation.

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.

Novel Prescribed Performance Control Scheme for Flexible Hypersonic Flight Vehicles with Nonaffine Dynamics and Neural Approximation

This study develops a novel neural-approximation-based prescribed performance controller for flexible hypersonic flight vehicles (HFVs). Firstly, a new prescribed performance mechanism is exploited, which develops new performance functions guaranteeing velocity and altitude tracking errors with small overshoots. Compared with the existing prescribed performance mechanism, it has better preselected transient and steady-state performance. Then, the nonaffine model of HFV is decomposed into a velocity subsystem and an altitude subsystem. A prescribed performance-based proportional-integral controller is designed in the velocity subsystem. In the altitude subsystem, the model is expressed as a nonaffine pure feedback form, and control inputs are derived from neural approximations. In order to reduce the amount of computation, only one neural network approximator is used to approximate the subsystem uncertainties, and an advanced regulation algorithm is applied to the devise adaptive law for neural estimation. At the same time, the complex design process of back-stepping can be avoided. Finally, numerical simulation results are presented to verify the efficiency of the design.

Guardian Map Approach to Feasible Range of Static Stability Margin of Hypersonic Flight Vehicles with Input Saturation

Static stability margin is a critical parameter in flight control design. The feasible range of it must cover the uncertainty through the flight. To reasonably identify the feasible range of static stability margin in advance, an approach based on guardian maps is proposed for flight control of hypersonic flight vehicles with input saturation. First, the model of hypersonic flight vehicle (HFV) is established as a parametric plant. Then, flying quality requirements for the closed-loop system are formulated as inequality constraints using guardian maps. Moreover, by using linear matrix inequality, the saturation of elevators is taken into account in the integrated control of attitude control. The prescribed minimum of static stability margin that ensures the flying quality of hypersonic flight vehicles with input saturation is obtained. Furthermore, from the prospective of integrated control, it is shown that the feasible range of static stability margin can be enlarged by changing aerodynamic characteristics. The effectiveness of the proposed approach is validated by numerical simulation.

Robust tracking control of hypersonic flight vehicles: A continuous model-free control approach

It is extremely difficult to establish precise motion model for hypersonic flight vehicles (HFVs). However, the majority of the existing control techniques focus on model-based methodologies. This paper investigates a novel model-free controller for a continuous non-affine model of HFV. Firstly, the nonaffine vehicle dynamics is transformed into a pure feedback formulation consisting of velocity subsystem and altitude subsystem. Then, a model-free tracking control law is exploited for velocity subsystem. Furthermore, the developed model-independent control technique is expanded into the altitude subsystem that is a high-order dynamic system. The proposed model-free controller contains a Hurwitz stable term and a filtering term. In addition, compensated filters are devised to further strength robustness. The special novelty is that the addressed controller doesn't require accurate affine model, exhibiting fine universal property and strong robustness. Finally, theoretical conclusions are validated and the effectiveness of the design is verified by simulation results.

Sensor cascading fault estimation and control for hypersonic flight vehicles based on a multidimensional generalized observer

SummaryThis study presents a sensor cascading fault estimation and fault‐tolerant control (FTC) for a nonlinear Takagi‐Sugeno fuzzy model of hypersonic flight vehicles. Sensor cascading faults indicate the occurrence of source fault will cause another fault and the interval between them is really short, which makes it difficult to handle them in succession. A novel multidimensional generalized observer is used to estimate faults by integrating constant offset and time‐varying gain faults. Then, a fault‐tolerant controller is used to solve system nonlinearity and sensor fault problems. The observer and controller satisfy the performance index and are robust to external disturbances. A sufficient condition for the existence of observer and controller is derived on the basis of Lyapunov theory. Simulation results indicate the effectiveness of the proposed fault estimation and FTC scheme.

Robust Adaptive Fuzzy Control for HFV With Parameter Uncertainty and Unmodeled Dynamics

This paper proposes a robust adaptive fuzzy tracking controller for a hypersonic flight vehicle (HFV) subject to both parametric uncertainties and unmodeled dynamics. First, the nonlinear model of HFV is input/ouput linearization and the internal dynamics of HFV are established. Second, the ideal internal dynamics (IID) are calculated and then an IID-based controller designing method is utilized. With considering parameter uncertainties and unmodeled dynamics, a full state tracking error system is built. Fuzzy logical system (FLS) is utilized to identify the nonlinear system with parameter uncertainty and unmodeled dynamics. An adaptive fuzzy controller is proposed to guarantee the stability of the whole system with parameter uncertainty and unmodeled dynamics. Comparison simulations show remarkable efficiency of the proposed method.

A fuzzy wavelet neural network-based approach to hypersonic flight vehicle direct nonaffine hybrid control

A direct nonaffine hybrid control methodology is proposed for a generic hypersonic flight models based on fuzzy wavelet neural networks (FWNNs). The addressed strategy extends the previous indirect nonaffine control approaches stemming from simplified models of affine formulations. To cope with nonaffine effects on control design, analytically invertible models are constructed and then novel hybrid controllers are developed directly using nonaffine models. Furthermore, by employing FWNNs to devise adaptive terms, inversion errors are canceled via fuzzy neural approximations. In addition, robust terms are designed to achieve larger stable region in comparison with earlier work using Lyapunov synthesis. Finally, numerical simulation results from a hypersonic flight vehicle model are given to clarify the efficiency of the proposed direct nonaffine control scheme in the presence of parametric uncertainties.

Adaptive Control of Hypersonic Flight Vehicles With Limited Angle-of-Attack

This paper designs a high-performance adaptive controller for the uncertain model of hypersonic flight vehicles (HFVs) proceed by faulty and hysteretic actuators. A parameterized HFV model is derived, based on which adaptive tracking controllers for velocity and altitude are designed, sequentially. Compared with other adaptive strategies that mainly focus on the parametric uncertainty and asymptotic tracking, utilization of the prescribed performance control technique can largely improve the transient characteristics of HFVs. A novel handling on angle-of-attack (AOA) is proposed with the help of barrier functions. As a result, the magnitude of AOA is limited to match the requirement of the scramjet. Partial loss of effectiveness (PLOE) of actuators is also taken into account, while the backlash hysteresis in aerodynamic control surfaces is accommodated by an adaptive inverse compensation. Corresponding analysis shows that both the limited AOA and the desired performance can be guaranteed despite PLOE of actuators. A simulation study is provided to verify the effectiveness of the proposed controller.

Nonlinear fuzzy fault-tolerant control of hypersonic flight vehicle with parametric uncertainty and actuator fault

This study presents a nonlinear fuzzy fault-tolerant control (FTC) and a fault observer for longitudinal dynamics of hypersonic flight vehicle (HFV) with parameter uncertainty and actuator gain loss fault via sliding-mode and backstepping theory. An affine nonlinear dynamic model of HFV with parameter uncertainty and actuator fault is established based on feedback linearization technology. A nominal sliding-mode control is developed to track the command of altitude and velocity. Unknown nonlinear functions in the controller are approximated by fuzzy logic system through updating the weight parameters online. In view of the occurrence of actuator fault, a backstepping sliding-mode observer is constructed to estimate the fault. A nonlinear fuzzy FTC is then designed with the estimate fault obtained from the observer to address the problem of actuator fault and parameter uncertainty. The stability of the controller is analyzed utilizing Lyapunov theory. Numerical simulation results demonstrate the validity and robustness of the proposed controller and observer.

LESO Based Dynamic Surface Control for Hypersonic Flight Vehicle

In the presence of model parametric uncertainties and external disturbances, a LESO-based dynamic surface control approach is designed for the longitudinal model of Hypersonic Flight Vehicle (HFV). Via Nonlinear Dynamic Inversion (NDI) technique, the decoupling of altitude and velocity is realized. Combining with conventional back-stepping technique, a low pass filter (LPF) is introduced to attain the derivation of virtual control laws, which avoids the problem of "differentiation explosion". A linear extended state observer (LESO) is designed for the precise estimation and compensation of "lumped disturbance" containing parametric uncertainties and external disturbances, which tremendously improves the ability of disturbance rejection of the system. The stability of the proposed approach is analyzed by means of Lyapunov theory. The simulation results demonstrate that the proposed methodology has good command tracking performance, and the approach is robust in the presence of lumped disturbances.

Nonlinear adaptive tracking control of non-minimum phase hypersonic flight vehicles with unknown input nonlinearity

A nonlinear adaptive controller design method for output tracking of hypersonic flight vehicles (HFVs) subject to input nonlinearity is proposed in this paper. The parameters of the input nonlinearity are assumed to be unknown. This problem is challenging because of the complex nonlinearity of HFVs and the existence of the unknown input nonlinearity. The nonlinear model of HFVs is linearized, and the internal dynamics of this model are constructed. Since the internal dynamics of HFVs are non-minimum, an ideal internal dynamics (IID)-based control strategy is utilized and a states tracking model is constructed based on the computed IID. Then a nonlinear adaptive control strategy is designed to guarantee the bounded of output tracking error in the existence of unknown input nonlinearity. Comparison simulation results are provided to verify the available of the proposed method.

Strictly-lower-convex-function-constructing disturbance observer based adaptive back stepping control for hypersonic flight vehicles

This study concerns with the attitude and velocity tracking control problem for the longitudinal model of hypersonic flight vehicles, which is nonlinear in aerodynamics with model uncertainties and external disturbances. By employing back stepping sliding mode method and the strictly-lower-convex-function-constructing nonlinear disturbance observer (SNDOB), a novel composite controller is proposed to guarantee the system tracking error to converge to a small region containing the origin. Besides, several proper adaptive laws are also introduced to make the controller avoid of the differential explosion problem and be chatter-free. Compared with other robust flight control approaches, key novelties of the developed method are that one new SNDOB is proposed and drawn into the virtual control laws at each step to compensate the disturbances and that adaptive laws are utilized to simplify the tedious and complicated differential operations. Finally, it is demonstrated by the simulation results that the new method exhibits not only an excellent robustness but also a better disturbance rejection performance than the convention approach.