Minimal-learning-parameter technique based adaptive neural control of hypersonic flight dynamics without back-stepping

Xu, Bin; Fan, Yonghua; Zhang, Shangmin

doi:10.1016/j.neucom.2015.02.069

Cited by 55 publications

(44 citation statements)

References 32 publications

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“…Besides the issues mentioned above, dynamic surface control is widely applied for HFVs. [10][11][12] Trajectory tracking problem is analyzed by using backstepping, in which intelligent algorithm with much less computation burden is applied by Xu et al 13,14 Neural network-based dynamic surface control strategy is applied in the HFV system. 15,16 Compared with the traditional dynamic surface control, neural network can estimate the complex control gain and system uncertain online, which need less information about the longitude dynamics.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fault tolerant control for hypersonic vehicle with external disturbance

Huang

2017

International Journal of Advanced Robotic Systems

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In this article, an adaptive fault tolerant control strategy is proposed to solve the trajectory tracking problem of a generic hypersonic vehicle subjected to actuator fault, external disturbance, and input saturation. The longitudinal model of generic hypersonic vehicle is divided into velocity subsystem and altitude subsystem, in which dynamic inversion and backstepping are applied, respectively, to track the desired trajectories. For the unknown maximum disturbance upper bound, actuator fault, and input saturation constraint, adaptive laws are proposed to estimate these information online. Finally, numeric simulation is conducted in the cruise phase for generic hypersonic vehicle. Simulation results show that the controllers designed in this article can make generic hypersonic vehicle track the desired trajectories in the presence of actuator fault, external disturbance, and input saturation.

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Section: Introductionmentioning

confidence: 99%

Adaptive fault tolerant control for hypersonic vehicle with external disturbance

Huang

2017

International Journal of Advanced Robotic Systems

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“…Thereby, the inequality given by equation (29) is satisfied when h -is chosen as the form of equation (30). Consequently, it is easy to prove that J 1 is Lipschitz.…”

Section: Novel Finite-time-convergent Differentiatormentioning

confidence: 97%

“…where w max is a positive constant, the system given by equation (30) is finite-time stable and the setting time T s satisfies the inequality given by equation (30). Proof.…”

Section: Novel Finite-time-convergent Differentiatormentioning

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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“…However, in practical application, large amount of update parameters results in the computation burden of online learning. In [20], the minimal-learning-parameter technique is further incorporated into the high gain observer to greatly reduce the online computation burden.…”

Section: Introductionmentioning

confidence: 99%

Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

Zhang

2017

Complexity

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This paper investigates an adaptive neural sliding mode controller for MEMS gyroscopes with minimal-learning-parameter technique. Considering the system uncertainty in dynamics, neural network is employed for approximation. Minimal-learningparameter technique is constructed to decrease the number of update parameters, and in this way the computation burden is greatly reduced. Sliding mode control is designed to cancel the effect of time-varying disturbance. The closed-loop stability analysis is established via Lyapunov approach. Simulation results are presented to demonstrate the effectiveness of the method.

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Minimal-learning-parameter technique based adaptive neural control of hypersonic flight dynamics without back-stepping

Cited by 55 publications

References 32 publications

Adaptive fault tolerant control for hypersonic vehicle with external disturbance

Adaptive fault tolerant control for hypersonic vehicle with external disturbance

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

Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

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