Extended Disturbance Observer With Measurement Noise Reduction for Spacecraft Attitude Stabilization

He, Tongfu; Wu, Zhong

doi:10.1109/access.2019.2918076

Cited by 18 publications

(10 citation statements)

References 45 publications

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“…Combining Eqs. (8,19) can obtain a robust control allocation optimization model with constraints as follows…”

Section: Robust Control Allocation Modelmentioning

confidence: 99%

“…The difficulty in robust stabilization about closed-loop system with uncertainties and exogenous random disturbances was solved when the average anisotropy is known [6]. In [7,8] , the spacecraft attitude control problem with measurement error was investigated, and a robust anti-disturbance control law and a noise reduction EDO build the foundation for an augmented disturbance representation were designed to convert the high stability attitude stabilization into reality [7,8]. A robust nonlinear controller was offered to redistribute a virtual control signal to the rest actuators when the faults happened [9,10].…”

Section: Introductionmentioning

confidence: 99%

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Robust Control Allocation Method for Uncertain Systems Based on the Algorithms of Maximum-minimum and Improved Fish Swarm

Yang

Tong

Fang

2022

Preprint

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In this paper, a novel robust control allocation method for a control system with uncertain parameters is proposed based on the algorithms of maximum-minimum and improved fish swarm. Based on the algorithm of maximum-minimum, the control allocation problem with an uncertain allocation matrix is transformed into the definite control allocation problem; then by using an improved fish swarm algorithm, the resultant control allocation problem is solved. Finally, the simulation results show that the proposed robust control allocation method has better robustness to system modeling uncertainty and possesses stronger anti-interference ability than the existing control allocation methods.

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“…Combining Eqs. (8,19) can obtain a robust control allocation optimization model with constraints as follows…”

Section: Robust Control Allocation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Control Allocation Method for Uncertain Systems Based on the Algorithms of Maximum-minimum and Improved Fish Swarm

Yang

Tong

Fang

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…However, in many existing systems, a realization of high gain DOBs is challenging due to the mechanical limit of the control input and observation noise. Furthermore, the actuator's service life may be shortened due to the chattering motion by estimation noise from the DOBs [8]. Conventional DOBs have a trade-off between disturbance suppression performance and noise sensitivity [4] under noisy environments.…”

Section: Introductionmentioning

confidence: 99%

Variable Forgetting Factor-Based Adaptive Kalman Filter With Disturbance Estimation Considering Observation Noise Reduction

2021

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This paper addresses the influence reduction of quantization and observation noises in a disturbance observer (DOB) technique. DOB is a disturbance estimation method that makes control systems robust. However, in implementing low-resolution sensors, disturbance estimates from DOB are considerably influenced by observation and quantization noises. In this paper, a novel DOB design method for simultaneous estimation of state and unknown disturbances, including the reduction of noise influences, is proposed. The proposed method is divided into two components. The first component is a Kalman filter (KF)-based DOB for simultaneous estimation of state and unknown disturbances. To improve the estimation performance through the KF-based DOB, a forgetting factor-based adaptive KF (FAKF) was employed. The second component is an adaptive law for the forgetting factor in the FAKF. The adaptive law is used for balancing the estimation accuracy and observation noise reduction. Simulation results involving various types of noise environments demonstrate the effectiveness of the proposed method.

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“…Thus the measurement uncertainty is also involved in the attitude controller design of combined spacecraft. In paper [25] and [26], the attitude control problem with measurement error was investigated, and a noise reduction extended disturbance observer and a finite-time integral sliding mode disturbance observer were used to estimate the integrated uncertainties, respectively. In this paper, two disturbance-observers-based dynamic surface control method is used to develop the virtual attitude control.…”

Section: Introductionmentioning

confidence: 99%

Robust Control Allocation in Attitude Fault-Tolerant Control for Combined Spacecraft Under Measurement Uncertainty

Huang

Duan

2019

IEEE Access

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Attitude control of combined service-target system in the post-capture phase has received great attention. A new attitude dynamics of the combined spacecraft with reaction wheels has been established in the author's former work, however, the measurement uncertainty in attitude and angular velocity and uncertainty in the reconfiguration matrix of reaction wheels have not been considered, which may cause huge impact on the system performance. In this paper, a novel combination of disturbance-observer-based dynamic surface control under measurement uncertainty and robust control allocation due to uncertain mass center is investigated for attitude stabilization of the combined spacecraft. Firstly, considering measurement uncertainty, inertia uncertainty, actuator fault and actuator saturation, a new attitude dynamics of combined spacecraft is established. Then, a virtual controller is designed and all the states in the closed-loop system converge to a small neighborhood of zero, where the lumped disturbance is compensated by two stable nonlinear disturbance observers and adverse effect of actuator saturation is addressed by a stable compensator. Finally, in consideration of uncertain location of mass center in the reconfiguration matrix, a LMI-based robust control allocation is employed to deal with the problem of distributing the three axis torques over the reaction wheels. Numerical simulations are presented to illustrate the effectiveness of the proposed method.

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Extended Disturbance Observer With Measurement Noise Reduction for Spacecraft Attitude Stabilization

Cited by 18 publications

References 45 publications

Robust Control Allocation Method for Uncertain Systems Based on the Algorithms of Maximum-minimum and Improved Fish Swarm

Robust Control Allocation Method for Uncertain Systems Based on the Algorithms of Maximum-minimum and Improved Fish Swarm

Variable Forgetting Factor-Based Adaptive Kalman Filter With Disturbance Estimation Considering Observation Noise Reduction

Robust Control Allocation in Attitude Fault-Tolerant Control for Combined Spacecraft Under Measurement Uncertainty

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