Nonlinear disturbance observer based robust backstepping control for a flexible air-breathing hypersonic vehicle

Wu, Guanghui; Meng, Xiuyun

doi:10.1016/j.ast.2016.04.018

Cited by 84 publications

(36 citation statements)

References 24 publications

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“…To reduce the chattering, the quasi-continuous high-order mode controllers are exploited, effectively reducing the flutter of the AHV [9]. By introducing the nonlinear disturbance observers (NDO), the total uncertainty is estimated online, and the robustness of the controller is guaranteed [10,11]. Noticing that the robustness of the designed controllers is closely related to the NDO, an novel NDO based on hyperbolic sine function is investigated and the robustness is enhanced [12].…”

Section: Introductionmentioning

confidence: 99%

Constrained Adaptive Neural Control for Air-Breathing Hypersonic Vehicles without Backstepping

Tan

Lei

Wang

2018

Mathematical Problems in Engineering

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An adaptive neural control scheme without backstepping is proposed for the air-breathing hypersonic vehicle subject to input constraints. To estimate the unknown nonlinearity of velocity subsystem and altitude subsystem, two radial basis function neural networks (RBFNNs) are constructed. Since the complex backstepping design steps are not needed, the proposed control structure is quite concise and the problem of "explosion of terms" is avoided. Moreover, a novel nonlinear auxiliary system is constructed to solve the problem of input constraints. The advantage of the proposed auxiliary system is that its high-order form has good performance and the parameter tuning is relatively easy. Simulation results show that the designed controllers achieve stable tracking of reference commands with good performance.

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Section: Introductionmentioning

confidence: 99%

Constrained Adaptive Neural Control for Air-Breathing Hypersonic Vehicles without Backstepping

Tan

Lei

Wang

2018

Mathematical Problems in Engineering

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“…In the past decades, non-linear control methods such as adaptive backstepping control, non-linear disturbance observer, and robust control were used to improve robustness of the reentry control systems Li et al, 2016;Wu and Meng, 2016). But, the system input and output constraints were not considered in Xu et al (2012), Li et al (2016), and Wu and Meng (2016).…”

Section: Introductionmentioning

confidence: 99%

“…But, the system input and output constraints were not considered in Xu et al (2012), Li et al (2016), and Wu and Meng (2016). Well-known methods for constrained control include antiwindup control and reference governors.…”

Section: Introductionmentioning

confidence: 99%

Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

Zhang

Sun

2017

Front. Robot. AI

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Citation:Zhang J, Sun T and Pan Y (2017) Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints. Front. Robot. AI 4:23. doi: 10.3389/frobt.2017 Designing robust control for hypersonic vehicles in reentry is difficult, due to the features of the vehicles including strong coupling, non-linearity, and multiple constraints. This paper proposed a characteristic model-based robust model predictive control (MPC) for hypersonic vehicles with reentry constraints. First, the hypersonic vehicle is modeled by a characteristic model composed of a linear time-varying system and a lumped disturbance. Then, the identification data are regenerated by the accumulative sum idea in the gray theory, which weakens effects of the random noises and strengthens regularity of the identification data. Based on the regenerated data, the time-varying parameters and the disturbance are online estimated according to the gray identification. At last, the mixed H 2 /H ∞ robust predictive control law is proposed based on linear matrix inequalities (LMIs) and receding horizon optimization techniques. Using active tackling system constraints of MPC, the input and state constraints are satisfied in the closed-loop control system. The validity of the proposed control is verified theoretically according to Lyapunov theory and illustrated by simulation results.

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“…[3][4][5][6][7] Benefiting from the cascade structure of HFV dynamics, a strict-feedback form of the altitude subsystem was obtained and then a backstepping technique was utilized to devise the state-feedback controller in the work by Wu and Meng and Xu et al [8][9][10] Although the backstepping technique has been evolved as an efficient control method for HFVs, tedious and complex analysis is required for virtual controllers and their repeated derivatives. This is the inherent drawback of backstepping, also referred to as "explosion of terms".…”

Section: Introductionmentioning

confidence: 99%

Efficient adaptive constrained control with time-varying predefined performance for a hypersonic flight vehicle

Wei

Luo

Dai

et al. 2017

International Journal of Advanced Robotic Systems

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A novel low-complexity adaptive control method, capable of guaranteeing the transient and steady-state tracking performance in the presence of unknown nonlinearities and actuator saturation, is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. In order to attenuate the negative effects of classical predefined performance function for unknown initial tracking errors, a modified predefined performance function with time-varying design parameters is presented. Under the newly developed predefined performance function, two novel adaptive controllers with low-complexity computation are proposed for velocity and altitude subsystems of the hypersonic flight vehicle, respectively. Wherein, different from neural network-based approximation, a least square support vector machine with only two design parameters is utilized to approximate the unknown hypersonic dynamics. And the relevant ideal weights are obtained by solving a linear system without resorting to specialized optimization algorithms. Based on the approximation by least square support vector machine, only two adaptive scalars are required to be updated online in the parameter projection method. Besides, a new finite-time-convergent differentiator, with a quite simple structure, is proposed to estimate the unknown generated state variables in the newly established normal output-feedback formulation of altitude subsystem. Moreover, it is also employed to obtain accurate estimations for the derivatives of virtual controllers in a recursive design. This avoids the inherent drawback of backstepping -"explosion of terms" and makes the proposed control method achievable for the hypersonic flight vehicle. Further, the compensation design is employed when the saturations of the actuator occur. Finally, the numerical simulations validate the efficiency of the proposed finitetime-convergent differentiator and control method.

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Nonlinear disturbance observer based robust backstepping control for a flexible air-breathing hypersonic vehicle

Cited by 84 publications

References 24 publications

Constrained Adaptive Neural Control for Air-Breathing Hypersonic Vehicles without Backstepping

Constrained Adaptive Neural Control for Air-Breathing Hypersonic Vehicles without Backstepping

Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

Efficient adaptive constrained control with time-varying predefined performance for a hypersonic flight vehicle

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