Attitude estimation and control based on modified unscented Kalman filter for gyro-less satellite with faulty sensors

Pourtakdoust, Seid H.; Mehrjardi, Mohamad Fakhari; Hajkarim, Mohammad Hossein

doi:10.1016/j.actaastro.2021.11.008

Cited by 21 publications

(8 citation statements)

References 30 publications

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“…Þ are the 2n þ 1 sigma sampling points obtained by substituting b x a kþ1jk and P a kþ1jk in Equation (22) into Equations ( 19) and ( 20); ξ i kþ1jk is obtained by transforming these sampling points through H a ; and b y a kþ1jk , P a yy,kþ1jk , and P a xy,kþ1jk are the one-step predicted mean, variance, and cross-covariance of the measurement variables, respectively.…”

Section: Time Update Is As Followsmentioning

confidence: 99%

“…Since this theory was proposed, it has attracted scholarly interest worldwide, yielding extensive research results. [22][23][24] In addition to dynamic system state estimation, the Kalman filter approach can be used for unknown parameter estimation. [25,26] The UKF algorithm abandons the traditional method of linearizing non-linear function and uses the unscented transform to deal with the non-linear transfer problem of mean and covariance.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic synergistic modelling for cobalt removal process in zinc hydrometallurgy and the research of parameter estimation based on unscented Kalman filter

Wang

Tang

et al. 2023

Can J Chem Eng

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The cobalt removal process with arsenic salt of zinc hydrometallurgy has serious non‐linearity, uncertainty, and mutual coupling. Its accurate dynamic modelling has always been a challenging problem. On the basis of in‐depth analysis of cobalt removal process and reaction mechanism, considering the cascade relationship between the reactors, a dynamic synergistic continuously stirred tank reactor (SCSTR) mechanism model of the cobalt removal process was constructed. Aiming at the unknown parameters in the SCSTR model, the idea of the Kalman filter was introduced, and the unknown parameters were characterized as unknown states; a method of estimating the unknown model parameters was developed using the augmented state equation and the unscented Kalman filter (UKF) algorithm. Simulation results with industrial data of a zinc smeltery showed that the parameter estimation model has high accuracy, and the estimated parameters can be used in the SCSTR model. An intensive simulation analysis of the dynamic characteristics of the complete SCSTR model was carried out to verify the influence of different input disturbances on the output ion concentration of each reactor, which demonstrated the excellent dynamic performance and potential of the model. Ultimately, according to the industrial calculation analysis, the SCSTR model has a guiding effect on the addition of zinc powder in the reactors, overcomes the blindness in the production process, and provides a momentous basis for the optimization control of the cobalt removal process.

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Section: Time Update Is As Followsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic synergistic modelling for cobalt removal process in zinc hydrometallurgy and the research of parameter estimation based on unscented Kalman filter

Wang

Tang

et al. 2023

Can J Chem Eng

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“…For the FTC of ACSs of satellites, the Kalman filter‐based method (Pourtakdoust et al., 2022) and the observer‐based methods (Fonod et al., 2015; S. Gao et al., 2020) have been proposed. However, these methods require beforehand estimation of states of ACSs of satellites, thereby needing to be further improved in terms of real‐time performance.…”

Section: Introductionmentioning

confidence: 99%

“…For the FTC of ACSs of satellites, the Kalman filter-based method (Pourtakdoust et al, 2022) and the observer-based methods (Fonod et al, 2015;S. Gao et al, 2020) have been proposed.…”

mentioning

confidence: 99%

Neuro‐Adaptive Finite Time Composite Fault Tolerant Control for Attitude Control Systems of Satellites

Wang,

Liang,

Yang

et al. 2023

Radio Science

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An adaptive finite time composite fault tolerant control strategy based on an optimized neural network for Attitude control systems (ACSs) of satellites is proposed considering the state time‐varying delays, concurrent actuator and sensor faults, system uncertainties, modelable external disturbance and operating noise. An uncertain time‐varying state space model for ACSs of satellites is established, and sensor faults are equivalent to actuator‐like faults. A disturbance observer is designed for estimating the modelable external disturbance, and an improved dwarf mongoose optimization (DMO) algorithm based on the Levy flight distribution is utilized to optimize the basis function of hyperbasis function neural networks to better estimate the augmented actuator faults that include the actuator fault and the actuator‐like fault. Furthermore, an adaptive finite time composite fault‐tolerant controller is proposed, which includes the delay‐dependent feedback control law, disturbance estimation based‐disturbance compensation law and the adaptive fault compensation law based on the augmented fault estimation using the improved DMO‐hyper basis function neural network. The finite time boundness of the close‐loop dynamics to the uncertainties, operating noise, and augmented actuator faults and the robustness of the measurement to the uncertainties, operating noise and augmented actuator faults are analyzed, and the observer and controller design is formulated as the linear matrix inequalities. Simulation examples for ACSs in different working conditions are considered to exhibit the proposed method's effectiveness.

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“…In this case, the KF directly selects the respective gain matrix based on the attitude control mode of the satellite. On the other hand, [ 11 ] introduces the square root-based UKF (SRUKF) algorithm with fault detection and identification (FDI) capabilities. The FDI detects and isolates any outlier measurement to ensure the stable performance of the SRUKF algorithm.…”

Section: Introductionmentioning

confidence: 99%

Simplex Back Propagation Estimation Method for Out-of-Sequence Attitude Sensor Measurements

Goh

Tissera

Tan

et al. 2022

Sensors

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For a small satellite, the processor onboard the attitude determination and control system (ADCS) is required to monitor, communicate, and control all the sensors and actuators. In addition, the processor is required to consistently communicate with the satellite bus. Consequently, the processor is unable to ensure all the sensors and actuators will immediately respond to the data acquisition request, which leads to asynchronous data problems. The extended Kalman filter (EKF) is commonly used in the attitude determination process, but it assumes fully synchronous data. The asynchronous data problem would greatly degrade the attitude determination accuracy by EKF. To minimize the attitude estimation accuracy loss due to asynchronous data while ensuring a reasonable computational complexity for small satellite applications, this paper proposes the simplex-back-propagation Kalman filter (SBPKF). The proposed SBPKF incorporates the time delay, gyro instability, and navigation error into both the measurement and covariance estimation during the Kalman update process. The performance of SBPKF has been compared with EKF, modified adaptive EKF (MAEKF), and moving–covariance Kalman filter (MC-KF). Simulation results show that the attitude estimation error of SBPKF is at least 30% better than EKF and MC-KF. In addition, the SBPKF’s computational complexity is 17% lower than MAEKF and 29% lower than MC-KF.

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Attitude estimation and control based on modified unscented Kalman filter for gyro-less satellite with faulty sensors

Cited by 21 publications

References 30 publications

Dynamic synergistic modelling for cobalt removal process in zinc hydrometallurgy and the research of parameter estimation based on unscented Kalman filter

Dynamic synergistic modelling for cobalt removal process in zinc hydrometallurgy and the research of parameter estimation based on unscented Kalman filter

Neuro‐Adaptive Finite Time Composite Fault Tolerant Control for Attitude Control Systems of Satellites

Simplex Back Propagation Estimation Method for Out-of-Sequence Attitude Sensor Measurements

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