Model Of Flexible Air-breathing Hypersonic Vehicle Research Articles

Prescribed performance fuzzy back-stepping control of a flexible air-breathing hypersonic vehicle subject to input constraints

The design of prescribed performance fuzzy back-stepping tracking control for a flexible air-breathing hypersonic vehicle (FAHV) with actuator constraints is discussed. Fuzzy logic systems (FLSs) are applied to approximate the lumped uncertainty of each subsystem of the FAHV model. Every FLS contains only one adaptive parameter that needs to be updated online with a minimal-learning-parameter scheme. The sliding mode differentiator is introduced to obtain the derivatives of the virtual control laws, which avoid the explosion of the differentiation term in traditional back-stepping control. To further improve the control performance, a prescribed performance function characterizing the error convergence rate, maximum overshoot and steady-state error is utilized for the output error transformation. In particular, novel auxiliary systems are explored to handle input saturation. Fuzzy backstep control has obvious advantages in system robustness, control accuracy and highly real-time. Finally, reference trajectory tracking simulations show the effectiveness of the proposed method regarding air-breathing hypersonic vehicle control applications.

An improved continuous sliding mode controller for flexible air‐breathing hypersonic vehicle

AbstractAn improved continuous sliding mode control algorithm is proposed for a flexible air‐breathing hypersonic vehicle (FAHV), including nonsingular fast fixed‐time sliding surface (NFFS) and dual‐layer adaptive continuous twisting reaching law (DACTL). Firstly, the nonlinear control‐oriented model of FAHV is processed using input/output feedback linearization method with the significant flexible effects modeling as unknown matched disturbances. Secondly, a novel NFFS is improved from conventional fixed‐time sliding surface by adjusting power exponent to accelerate convergence rate. In the meanwhile, in order to avoid singularity aroused by fractional power term, an exponential convergent sliding surface is switched when tracking error approaches zero. Thirdly, a DACTL is proposed to realize finite‐time convergence of sliding mode variable with higher convergence precision and less chattering. Dual‐layer adaptive law is utilized to adjust the gain in DACTL based on equivalent control concept so as to enhance robustness automatically and avoid overestimation of control gain. Meanwhile, disturbances can be compensated without knowledge of Lipschitz constants. Ultimately, simulations on longitudinal control of FAHV demonstrate the control algorithm proposed is superior to conventional quasi‐continuous sliding mode controller in the aspect of convergence accuracy and chattering suppression.

Adaptive higher order super-twisting control algorithm for a flexible air-breathing hypersonic vehicle

A novel adaptive higher order super-twisting control algorithm (AHOSTC) is proposed for a flexible air-breathing hypersonic vehicle (FAHV). Firstly, the nonlinear control-oriented model (COM) is processed using input/output feedback linearization method. Therefore, significant flexible effects aroused by slender fuselage and strong coupling between propulsion and aerodynamic of FAHV could be considered during the application of model-based control techniques. Secondly, an adaptive control gain L is incorporated into normal higher order super-twisting algorithm (HOSTA) via dilation rescaling to improve speed of response and attenuate chattering, in the meanwhile, the matched disturbances can be compensated and the finite-time convergence can be achieved. In addition, gain L could be adjusted by the presented novel adaptive law automatically, especially when Lipschitz constants of disturbances are unknown and time-varying. Furthermore, the stability of adaptive law is analyzed via Lyapnuov criteria. Ultimately, compared with normal HOSTA, the proposed AHOSTC is able to enhance robustness and respond speed, while minimizing effects of chattering efficiently. Simulations on longitudinal model of FAHV are carried out to compare AHOSTC with normal HOSTA. The results demonstrate the superiority and effectiveness of AHOSTC under different simulation conditions, external disturbances and parametric uncertainties.

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories. The highlight is that the transient performance of velocity and altitude tracking errors is satisfactory and the computational load of neural approximation is low. Finally, numerical simulation results from a nonlinear FAHV model demonstrate the efficacy of the proposed strategy.

Novel auxiliary error compensation design for the adaptive neural control of a constrained flexible air-breathing hypersonic vehicle

This paper investigates the design of auxiliary error compensation for adaptive neural control of the longitudinal dynamics of a flexible air-breathing hypersonic vehicle (FAHV) with magnitude constraints on actuators. The control objective pursued is to steer velocity and altitude to follow their respective reference trajectories in the presence of actuator saturation and system uncertainties. To guarantee the exploited controller’s robustness with respect to parametric uncertainties, neural network (NN) is applied to approximate the lumped uncertainty of each subsystem of FAHV model. Different from the traditional parameter updating technique, in this paper, the minimal-learning-parameter (MLP) scheme is introduced to estimate the norm rather than the elements of NN’s weight vector while the computational load is reduced. The special contribution is that novel auxiliary systems are developed to compensate both the tracking errors and desired control laws, based on which the explored controller can still provide effective tracking of velocity and altitude commands when the actuators are saturated. Finally, numerical simulations are performed to illustrate the command tracking performance of the proposed strategy.

Super twisting sliding mode control for a flexible air-breathing hypersonic vehicle based on disturbance observer

A robust finite time sliding mode control strategy is proposed in this paper for a flexible air-breathing hypersonic vehicle (FAHV) model with aerodynamic parameter uncertainty. The strong coupling among the aerodynamics, the propulsion system and the flexibility effects makes the problem more challenging. Firstly, to reduce the complexity of the controller design, the FAHV model is transformed into three subsystems (velocity subsystem, altitude and flight path angle subsystem, attack of angle and pitch rate subsystem). Secondly, based on super-twisting algorithm, a novel finite time disturbance observer and an improved sliding mode controller are designed to ensure the finite time stability of each subsystem. The proposed disturbance observer can estimate the uncertainty and the derivative of virtual control in finite time. Finally, simulation results are presented to show the precision and rapidness in tracking the reference trajectory and validate the effectiveness of the designed controller.

Nonlinear Controller Design for Hypersonic Vehicles Based on Dynamic Inversion Considering Flexible States

This paper describes a nonlinear adaptive dynamic inversion controller for a flexible air-breathing hypersonic vehicle model. The complete characterization of the nonlinear internal dynamic of the Bolender and Doman model with respect to velocity，altitude and angle as the regulated outputs is considered in this paper. The derivation of the internal dynamics presented in this work is comprehensive of the flexible dynamics. For the purpose of control design，we decompose the equations of motion into functional subsystems，namely，the velocity subsystem，the altitude and flight-path angle subsystem，and the angle of attack and pitch rate subsystem. Each subsystem is controlled separately using available inputs and intermediate virtual control commands. The adaptive fuzzy system is then developed to identify the uncertain in the model parameters. Simulation results are provided to demonstrate the robustness and the efficacy of the proposed controller

Nonlinear Robust Adaptive Control of Flexible Air-Breathing Hypersonic Vehicles

This paper describes the design of a nonlinear robust adaptive controller for a flexible air-breathing hypersonic vehicle model. Because of the complexity of a first-principle model of the vehicle dynamics, a control-oriented model is adopted for design and stability analysis. This simplified model retains the dominant features of the higher-fidelity model, including the nonminimum phase behavior of the flight-path angle dynamics, the flexibility effects, and the strong coupling between the engine and flight dynamics. A combination of nonlinear sequential loop closure and adaptive dynamic inversion is adopted for the design of a dynamic state-feedback controller that provides stable tracking of the velocity and altitude reference trajectories and imposes a desired set point for the angle of attack. A complete characterization of the internal dynamics of the model is derived for a Lyapunov-based stability analysis of the closed-loop system, which includes the structural dynamics. The proposed methodology addresses the issue of stability robustness with respect to both parametric model uncertainty, which naturally arises when adopting reduced-complexity models for control design, and dynamic perturbations due to the flexible dynamics. Simulation results from the full nonlinear model show the effectiveness of the controller.