DOB-Based Neural Control of Flexible Hypersonic Flight Vehicle Considering Wind Effects

Xu, Bin; Wang, Danwei; Zhang, Youmin; Shi, Zhongke

doi:10.1109/tie.2017.2703678

Cited by 204 publications

(87 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consider the HFV altitude system (3) with control laws (5), (8), (11), and (13) and adaptive laws (12) and (14); all of the error signals are uniformly ultimately bounded.…”

Section: Stability Analysismentioning

confidence: 99%

See 1 more Smart Citation

Neural Back-Stepping Control of Hypersonic Flight Vehicle with Actuator Fault

Guo

2018

Journal of Control Science and Engineering

View full text Add to dashboard Cite

This paper addresses the fault-tolerant control of hypersonic flight vehicle. To estimate the unknown function in flight dynamics, neural networks are employed in controller design. Moreover, in order to compensate the actuator fault, an adaptive signal is introduced in the controller design to estimate the unknown fault parameters. Simulation results demonstrate that the proposed approach could obtain satisfying performance.

show abstract

“…Consider the HFV altitude system (3) with control laws (5), (8), (11), and (13) and adaptive laws (12) and (14); all of the error signals are uniformly ultimately bounded.…”

Section: Stability Analysismentioning

confidence: 99%

“…Therefore, back-stepping method [12][13][14] in HFV control has been widely studied. To eliminate continuous derivatives of each virtual control in back-stepping design, multiple methods such as dynamic surface control [15] and differentiator [14] are combined with back-stepping which makes the approach practicable.…”

Section: Introductionmentioning

confidence: 99%

Neural Back-Stepping Control of Hypersonic Flight Vehicle with Actuator Fault

Guo

2018

Journal of Control Science and Engineering

View full text Add to dashboard Cite

show abstract

“…Then the reinforcement learning was applied to address these uncertainties by using a critic NN and an action NN. The hypersonic flight vehicle control was investigated in [98] where the aerodynamic uncertainties and unknown disturbances were addressed by a disturbance observer based NN. In [99], a neural learning control was embedded in the HFV controller to achieve the global stability via a switching mechanism and a robust controller.…”

Section: Nn Based Robot Control With Input Nonlinearitiesmentioning

confidence: 99%

A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Jiang

Yang

et al. 2017

Complexity

View full text Add to dashboard Cite

As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.

show abstract

“…Furthermore, HFVs are more sensitive to the influence of external disturbances and uncertainties than other aircraft; thus, they have higher demand for robustness . Therefore, numerous research and verification works have been conducted in the past 20 years to meet the stability, safety, and reliability requirements …”

Section: Introductionmentioning

confidence: 99%

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Chen

Gong

2019

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

Summary This study proposes an improved adaptive fault diagnosis and compensation scheme for multisensor faults of hypersonic flight vehicles (HFVs). The faults are detected and isolated through a series of sensor output residuals and thresholds that consider observation error and disturbances. Via an adaptive augmented observer, the faults are estimated accurately and a time‐varying disturbance is handled by an additional differential part. Sensor faults are compensated on the basis of estimation results, and disturbances are considered in the fault‐tolerant control (FTC) design, thereby improving the tracking accuracy of the altitude and velocity and robustness with respect to external disturbances for HFVs. The stability of diagnosis and FTC is analyzed by Lyapunov theory. Numerical simulation results explain the validity of the proposed diagnosis and compensation methods.

show abstract

DOB-Based Neural Control of Flexible Hypersonic Flight Vehicle Considering Wind Effects

Cited by 204 publications

References 41 publications

Neural Back-Stepping Control of Hypersonic Flight Vehicle with Actuator Fault

Neural Back-Stepping Control of Hypersonic Flight Vehicle with Actuator Fault

A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Contact Info

Product

Resources

About