Control Of Air-breathing Hypersonic Vehicles Research Articles

Event-triggered hierarchical learning control of air-breathing hypersonic vehicles with predefined-time convergence

Event-triggered hierarchical learning control of air-breathing hypersonic vehicles with predefined-time convergence

Fault-tolerant learning control of air-breathing hypersonic vehicles with uncertain parameters and actuator faults

This paper investigates fault-tolerant learning control for air-breathing hypersonic vehicles (AHVs) subject to parametric uncertainties, external disturbances, and actuator faults. By treating the flexible dynamics as equivalent disturbance, the AHV model can be decomposed into velocity subsystem and altitude subsystem. An intelligent fault diagnosis approach is deployed to estimate the actuator fault information for each subsystem sequentially. Furthermore, combined with a fixed-time neural disturbance observer, composite learning control is deployed to construct control commands using the historical stack to improve the learning accuracy, while compensating for lumped disturbances, including fault diagnosis errors and external disturbances. The designed controller addresses the fault-tolerant tracking problem by combining offline and online learning strategies, which is a significant advantage over other existing AHV controllers. Simulation results validate the effectiveness of the fault-tolerant learning control.

Koopman-operator-based learning control of air-breathing hypersonic vehicles with nonminimum phase properties

In this article, a prescribed learning controller is developed for nonminimum phase air-breathing hypersonic vehicles (AHVs) in the presence of parametric uncertainties and external disturbances. In comparison with the current state of the art, the most significant feature of our control design lies in introducing the Koopman operator to construct an intelligent output redefinition to overcome the nonminimum phase behavior. To evaluate the current control behavior and enhance the learning ability, an improved continuous-time performance index is developed under the actor–critic learning structure. Furthermore, combined with a nonlinear disturbance observer, prescribed learning control is proposed to design control commands, while compensating for lumped disturbances, including neural approximation errors and external disturbances. Numerical simulations have been performed to highlight the superiority of the proposed learning control.

Variable-horizon predictive tracking control for air-breathing hypersonic vehicle based on composite disturbance observer

In this paper, a variable-horizon predictive tracking control (VHPTC) scheme based on composite disturbance observer (CDO) is proposed to investigate the attitude tracking problem for an air-breathing hypersonic vehicle (AHV) subject to external matched and mismatched disturbances. An explicit predictive tracking control term with the variable horizon is employed to reduce the online computation and improve the control performance of the AHV system. To comprehensively suppress the negative influences caused by the matched and mismatched disturbances, a CDO is constructed to estimate the unknown disturbances. Moreover, to further guarantee the stability of the closed-loop system affected by the resulting disturbance estimation error, the auxiliary control term is presented. Combining the predictive tracking control term with the variable horizon, the auxiliary control term, and the disturbance compensation control term obtained by CDO, the entire VHPTC law for the AHV system is obtained. Through the Lyapunov analysis, the rigorously exponential stability of the closed-loop system is ensured by the proposed CDO-based VHPTC scheme. The simulation results demonstrate the effectiveness of the presented strategy for the AHV attitude system.

Fast inner-loop control of air-breathing hypersonic vehicles

This paper investigates the inner-loop attitude and velocity control problem for air-breathing hypersonic vehicles subject to practically constrained actuators. Traditional nonlinear dynamic inverse (NDI) is enhanced by an intelligent control allocation (ICA) to realise the low-complexity attitude decoupling. The ICA addresses various characteristics of aerodynamic control surfaces while providing an efficient detecting mechanism for allocation errors. Within the ICA-NDI frame, a finite-time disturbance observer-based terminal sliding mode (FTDO-based TSM) attitude controller regulates Euler angles in the fast manner. This attitude controller employs an improved integral sliding surface containing necessary information from both ICA detection and FTDO estimation, which, therefore, is capable of accommodating constrained control surfaces and rejecting mismatched disturbances. Meanwhile, an adaptive governor adjusts the velocity reference according to the current saturation level of the scramjet fuel-to-air equivalency ratio. The governor is further integrated to a baseline adaptive velocity controller to synthetically handle scramjet input saturations and uncertain factors.

Neural Sliding Mode Tracking Control of Air-breathing Hypersonic Vehicles

This paper proposes a neural sliding mode control method for the tracking problem of the longitudinal dynamics of air-breathing hypersonic vehicles (ABHV). Considering the input/output feedback linearization, a high-order sliding mode law of the elevator deflection and the fuel equivalence ratio is designed. Moreover, the effect of uncertain model and control input disturbances is approximated with a Radial Basis Function Neural Network (RBFNN). The stability of the closed-loop system is analysed based on Lyapunov theorem. Simulation results shows the good tracking performance of the proposed controller and robustness with parameter uncertainties. All the signals are globally bounded and converged in short time.

Anti-Disturbance Dynamic Surface Control for Air-Breathing Hypersonic Vehicles Based on NDO

This paper is concerned with the anti-disturbance dynamic surface controller (DSC) design for an air-breathing hypersonic vehicle (AHV) based on nonlinear disturbance observer (NDO). For the longitudinal model of AHV subjected to the high nonlinearity, the uncertain parameters and the varying disturbance, the feedback linearization method is employed considering the uncertain parameters. Then, a dynamic surface controller is designed based on the inverse hyperbolic sine function to solve the problem of "explosion of terms" in the traditional backstepping control. Furthermore, in order to enhance the disturbance rejection ability, a novel NDO is designed to estimate the model uncertainties and external disturbances. Finally, the simulation results verify the superior tracking performance of the proposed control strategy.

Fixed-time adaptive general type-2 fuzzy logic control for air-breathing hypersonic vehicle

This paper proposes a novel fixed-time adaptive general type-2 fuzzy logical control (FAGT2FLC) scheme for an air-breathing hypersonic vehicle (AHV) with uncertainties. Firstly, the AHV dynamic model is transformed into a strict feedback form. Then, the FAGT2FLC is designed based on the transformed model to improve robustness and guarantee fixed-time convergence of the closed-loop system. The general type-2 fuzzy logic system (GT2FLS) is utilized to approximate the model uncertainties; for the purpose of designing adaptive laws, the [Formula: see text]-plane method is employed to represent the GT2FLS. A parameter projection operator is used to solve the possible singularity problem of parameter adaption. Besides, a fixed-time differentiator is used to deal with the “explosion of terms” inherent in backstepping method. Theoretical analysis based on relevant lemmas shows that the closed-loop system will converge into a small error band in fixed time. Lastly, detailed simulations are carried out to demonstrate the effectiveness and superiority of the proposed control scheme.

Adaptive Backstepping Sliding Mode Control of Air-Breathing Hypersonic Vehicles

In this paper, a controller combining backstepping and adaptive supertwisting sliding mode control method is proposed for altitude and velocity tracking control of air-breathing hypersonic vehicles (AHVs). Firstly, the nonlinear longitudinal model of AHV is introduced and transformed into a strict feedback form, to which the backstepping method can be applied. Considering the longitudinal trajectory tracking control problem (altitude control and velocity control), the altitude tracking control system is decomposed to several one-order subsystems based on the backstepping method, and an adaptive supertwisting sliding mode controller is designed for each subsystem, in order to obtain the virtual control variables and actual control input. Secondly, the overall stability of the closed-loop system is proved by the Lyapunov stability theory. At last, the simulation is carried out on an AHV model. The results show that the proposed controller has good control performances and good robustness in the parameter perturbation case.

Simplified longitudinal control of air-breathing hypersonic vehicles with hybrid actuators

This paper considers the longitudinal compound control of air-breathing hypersonic vehicles configured with hybrid aerodynamic control surface (ACS) and reaction control system (RCS). In the altitude loop, the proposed nonadaptive back-stepping design results in a simplified ACS-RCS compound control. This is attributable to the introduced tangent tracking errors and ACS-RCS fusion algorithm. ACS nonlinearity, RCS quantization, and modeling parametric uncertainties are handled. In the velocity loop, the performance guaranteed adaptive control is enhanced with the bound estimation mechanism, which accommodates modeling parametric uncertainties with a low dynamic order. The effectiveness of the proposed control is verified via simulations.

Adaptive Compound Control of Air-Breathing Hypersonic Vehicles

When working at extremely high altitude, aerodynamic surfaces of air-breathing hypersonic vehicles (AHVs) may not provide sufficient control authority. To remedy this shortage, we consider AHVs equipped with the auxiliary reaction control system (RCS), which utilize a set of control jets to compensate for ineffective aerodynamic surfaces. A novel longitudinal compound control is proposed to generate commands of aerodynamic surfaces and RCS, adaptively. Constrained angle-of-attack, uncertain parameters, and flexible dynamics are also considered.

Guaranteeing prescribed performance fast tracking control of air-breathing hypersonic vehicles

This paper investigates a fast-tracking controller with prescribed performance for flexible air-breathing hypersonic vehicles subject to uncertain parameters, external disturbances, actuator faults and backlash non-linearity. For the velocity and altitude dynamics, a prescribed performance control scheme is respectively utilized to provide preselected bounds on the transient and steady characteristics of tracking errors, also it can effectively relieve the constraint of scramjet on the angle of attack. A sliding mode exact observer is introduced to estimate the lumped disturbance, meanwhile the analytic differential computation on virtual controllers is avoided in the back-stepping design for altitude tracking. Based on prescribed performance control and sliding mode exact observer, the non-singular fast terminal sliding mode technology is introduced to design a control law, which is capable of ensuring both velocity and altitude tracking errors converge into the prescribed sets in finite-time. Simulations on the high-fidelity air-breathing hypersonic vehicle mode are implemented to highlight the effectiveness of the developed controller.

Lines cluster approaching mode control for air-breathing hypersonic vehicle under disturbances and uncertainties

This paper investigates the velocity and altitude tracking control problem for air-breathing hypersonic vehicle (AHV) in the presence of external disturbances and parameter uncertainties. A composite controller containing improved lines cluster approaching mode control (LCAMC) and nonlinear disturbance observer (NDO) is developed to guarantee the tracking errors converge to zero and enhance the robustness of control system. Meanwhile, considering the multiple uncertain parameters, a genetic algorithm (GA) based Pareto uncertainty estimation is employed to predict the parameter uncertainties of the AHV dynamics. Besides, the mathematical proofs of proposed method are analyzed by utilizing Lyapunov theory. Simulation results demonstrate the effective tracking performance, excellent disturbance estimation and uncertainty estimation ability of the composite method.

Self-repairing control of air-breathing hypersonic vehicle with actuator fault and backlash

In this article, self-repairing control is formulated for the longitudinal dynamics of flexible air-breathing hypersonic vehicles (AHVs) subject to a lumped effect of external disturbances, parametric uncertainties, actuator faults and backlash nonlinearities. Auxiliary systems are initially constructed to tackle the effects of magnitude constrain on actuators, which can modify the reference trajectories dynamically when actuators become saturated. Furthermore, fuzzy observers (FOs) are utilized to compensate the lumped obstacles online, which can rapidly render the disturbance estimate errors convergent. Sliding mode (SM) controllers based on FOs are sequentially designed, the selected SM laws can ensure the controllers are smooth and differentiable with minimal chattering. The stability of the closed-loop system is analyzed via Lyapunov theory. In the end, numerical simulation results are presented to demonstrate the efficacy of the design scheme.

Active Disturbance Rejection Control for Air-Breathing Hypersonic Vehicles Based on Prescribed Performance Function

Aiming at the longitudinal motion model of the air-breathing hypersonic vehicles (AHVs) with parameter uncertainties, a new prescribed performance-based active disturbance rejection control (PP-ADRC) method was proposed. First, the AHV model was divided into a velocity subsystem and altitude system. To guarantee the reliability of the control law, the design process was based on the nonaffine form of the AHV model. Unlike the traditional prescribed performance control (PPC), which requires accurate initial tracking errors, by designing a new performance function that does not depend on the initial tracking error and can ensure the small overshoot convergence of the tracking error, the error convergence process can meet the desired dynamic and steady-state performance. Moreover, the designed controller combined with an active disturbance rejection control (ADRC) and extended state observer (ESO) further enhanced the disturbance rejection capability and robustness of the method. To avoid the differential expansion problem and effectively filter out the effects of input noise in the differential signals, a new tracking differentiator was proposed. Finally, the effectiveness of the proposed method was verified by comparative simulations.

Barrier Lyapunov function based reinforcement learning control for air-breathing hypersonic vehicle with variable geometry inlet

Based on barrier Lyapunov functions, a reinforcement learning control method is proposed for air-breathing hypersonic vehicles with variable geometry inlet (AHV-VGI) subject to external disturbances and diversified uncertainties. The longitudinal dynamic for the AHV-VGI is transformed into strict feedback form. Controllers for velocity and altitude subsystems are designed, respectively. Taking advantage of the reinforcement learning strategy, two radial basis function (RBF) neural networks are applied to estimate the “total disturbances” in the flight control system. Actor network is used for generating the estimate of the disturbance. Critic network is used for evaluating the estimation accuracy. Prescribed tracking performances and state constraints can be guaranteed by introducing barrier Lyapunov functions (BLFs). Tracking differentiators are used to generate the derivatives of virtual controllers in the backstepping design process. Simulation results illustrate the effectiveness and advantages of the proposed control strategy.

ESO-based fault-tolerant anti-disturbance control for air-breathing hypersonic vehicles with variable geometry inlet

The fault-tolerant anti-disturbance control problem for air-breathing hypersonic vehicles with variable geometry inlet (AHV-VGI) is investigated. The VGI technique enlarges the AHV flight envelope at the expense of the system to inevitably possess unknown disturbances, model uncertainties and actuator faults. A novel fault-tolerant control strategy is proposed under the back-stepping control scheme based on extended state observer (ESO) and dynamic inversion. In each step, two ESOs are designed. The first one estimates the virtual control signals, and the second one approximates the total uncertainties. Dynamic inversion is introduced into the controller to deal with the non-affine actuator faults. In particular, the ESOs are activated successively in the designed controller. ESO estimation errors and output tracking errors of the AHV-VGI system are proved to be arbitrarily small in theory. Simulation results are provided to demonstrate the effectiveness and superiority of the proposed control strategy.

Envelope-constraint-based tracking control of air-breathing hypersonic vehicles

In this paper, a novel envelope-constraint-based neural controller is addressed for air-breathing hypersonic vehicles with unknown non-affine formulations. The vehicle dynamics is decomposed into velocity subsystem and altitude subsystem that are further described as unknown non-affine expressions. Neural networks are employed to approximate the unknown terms of each subsystem based on Mean Value Theorem, which rejects system uncertainties and non-affine characteristics. New learning algorithms are developed for adaptive parameters to stabilize the closed-loop system and reduce online parameters, yielding a low computational load design. The remarkable advantages are that complicated design procedure of back-stepping is avoided, and desired transient performance is guaranteed for velocity and altitude tracking errors via envelope constraint. The stability of closed-loop control system is proved utilizing Barrier Lyapunov functions. Finally, numerical simulation results are presented to validate the effectiveness of the proposed control approach.

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.

Multiple Lyapunov function-based longitudinal maneuver control of air-breathing hypersonic vehicles

For the longitudinal maneuver mission of air-breathing hypersonic vehicles, this paper develops an adaptive control strategy based on multiple Lyapunov function method. A switched model is applied to describe vehicle dynamics within the admissible range of velocity and altitude, as well as to make a proper tradeoff between modelling accuracy and design complexity. In comparison to the existing common Lyapunov function-based control, the proposed control is less conservative and requires relatively small input by directly identifying uncertain parameters in the switched model. Moreover, the tedious analytical differentiations in back-stepping are bypassed by the integration of dynamic surface control and online differentiator technique. A simulation study is provided to verify the proposed control.