Robust adaptive fuzzy control design for nearspace vehicle

He, Ning; Gao, Qian; Shen, Lin; Yao, Ke-Thia; Jiang, Changsheng

doi:10.3233/ifs-151953

Cited by 5 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A novel fuzzy robust tracking control strategy for anti-disturbance attitude control of NSV referring to the feedforward controller design of linear system was presented in He et al. 9 In Gao et al., 10 a robust reliable controller using fuzzy control technique was presented for NSV with parametric uncertainties and actuator faults. A robust tracking controller for NSV attitude control problem with external time-varying disturbances using backstepping and disturbance observer methods was proposed in Chen and Jiang.…”

Section: Introductionmentioning

confidence: 99%

Neural network based optimal adaptive attitude control of near-space vehicle with system uncertainties and disturbances

Xia

2018

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

In this paper, a neural network based optimal adaptive attitude control scheme is derived for the near-space vehicle with uncertainties and external time-varying disturbances. Firstly, radial basis function neural network (RBFNN) approximation method and nonlinear disturbance observer (NDO) are used to tackle the system uncertainties and external disturbances, respectively. Subsequently, a feedforward control input under backstepping control frame with RBFNN and NDO is designed to transform the optimal tracking control problem into an optimal stabilization problem. Then, a single online approximation based adaptive method is used to learn the Hamilton–Jacobi–Bellman equation to obtain the corresponding optimal controller. As a result, the compound controller consists of feedforward control input and optimal controller which can ensure that the near-space vehicle attitude angles are able to track reference signals in an optimal way. Lyapunov stability analysis method is used to show that all the closed-loop system signals are uniformly ultimately bounded. Finally, simulation results show the effectiveness of the proposed optimal attitude control scheme.

show abstract

Section: Introductionmentioning

confidence: 99%

Neural network based optimal adaptive attitude control of near-space vehicle with system uncertainties and disturbances

Xia

2018

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

show abstract

“…[27][28][29] This control scheme is an efficient way to deal with the model uncertainties and external disturbances even if the boundaries of uncertainties and disturbances are unknown. Furthermore, FLS are always combined with other control approaches, such as robust control, 30 adaptive control, 31 fault tolerant control, 32 and so on, which can improve the attitude tracking performance of the closed-loop system and achieve a good robustness characteristic simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Attitude control design for reusable launch vehicles using adaptive fuzzy control with compensation controller

Mao

Dou

Zong

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

This paper describes the design of attitude control for reusable launch vehicles during reentry phase using adaptive fuzzy control strategy with compensation controller that assures a stable and accurate attitude tracking despite having parameter uncertainties and external disturbances in the plant model. Firstly, the six-degrees-of-freedom dynamic model of the reusable launch vehicles is established, followed by a model transformation of rotational and kinematic dynamic equations, which results in a strict-feedback form attitude control system. Secondly, a fuzzy logic system combined with the adaptive technique is employed to model the system uncertainty term online. Then an attitude tracking controller based on adaptive fuzzy control approach is designed to assure tracking of guidance commands. Furthermore, to attenuate the adverse effects of fuzzy modeling errors on the control performance and system stability, a compensation controller is introduced to the control strategy. In addition, the stability of the closed-loop system is proved by using the Lyapunov theory, and the attitude tracking error converges to a small neighborhood of the origin. Finally, the simulation results and discussions are provided to verify the effectiveness of the proposed control strategy in tracking the guidance commands.

show abstract

Fuzzy terminal sliding-mode control for hypersonic vehicles

Gutiérrez

Gao

et al. 2017

IFS

View full text Add to dashboard Cite

Robust adaptive fuzzy control design for nearspace vehicle

Cited by 5 publications

References 19 publications

Neural network based optimal adaptive attitude control of near-space vehicle with system uncertainties and disturbances

Neural network based optimal adaptive attitude control of near-space vehicle with system uncertainties and disturbances

Attitude control design for reusable launch vehicles using adaptive fuzzy control with compensation controller

Fuzzy terminal sliding-mode control for hypersonic vehicles

Contact Info

Product

Resources

About