Attitude control of spacecraft simulator without angular velocity measurement

Malekzadeh, Maryam; Sadeghian, Hamid

doi:10.1016/j.conengprac.2018.11.011

Cited by 19 publications

(14 citation statements)

References 24 publications

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“…This simulator consists of four section: AHRS sensor, integrated computer, actuating dc motors, and four reaction wheels with the moment of inertia I w = 0.0021 kg•m 2 [20]. (B) Angular velocities, feedback linearization [20]. (C) Control efforts, feedback linearization [20].…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…To show the ability of this hybrid controller, hybrid controller in this article is compared with a feedback linearization controller (FLC) in Malekzadeh and Sadeghian [20]. Comparing Figure 5A,D (FLC, in normal conditions) and Figure 3A,D (hybrid controller, in uncertain conditions), there is a large difference between experimental and simulation results in FLC while in the proposed hybrid controller, this difference is a little because of robustness.…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…The reaction wheels are used as control actuator. The total angular spacecraft simulator is the sum of angular momentum of the platform and the actuators expressed as (1) [10,11]:…”

Section: Spacecraft Simulator Dynamic Equationmentioning

confidence: 99%

“…The reaction wheels are used as control actuator. The total angular spacecraft simulator is the sum of angular momentum of the platform and the actuators expressed as () [10, 11]:

{boldh}_{t} = boldJ boldω + {boldh}_{w},

where

boldJ, bold-italicω

, and h w are the platform inertia matrix, angular velocity vector, and angular momentum of reaction wheels, respectively. By applying the Euler dynamic equation in the body coordinate, () is yield:

{bold-italicτ}_{d} = {\overset{boldh}{true}}_{t} + boldω \times {boldh}_{t},

where

{bold-italicτ}_{d}

is the total disturbance torque acting on the simulator, expressed through ():

{bold-italicτ}_{d} bold= {boldd}_{0} + m g ((), {boldr}_{s} \times boldk),

where

{boldr}_{s} = ([], \begin{matrix} center center center \\ array r_{x} & array r_{y} & array r_{z} \end{matrix})

and k and d 0 are a position vector from the platform rotation center to its mass‐center, a unit vector in the direction of gravity and unmodeled disturbances, respectively.…”

Section: Spacecraft Simulator Dynamic Equationmentioning

confidence: 99%

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Finite‐time control of spacecraft and hardware in the loop tuning

Ali

Malekzadeh

Ataei

2022

Asian Journal of Control

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A nonlinear disturbance observer based on a super twisting controller is designed and implemented on the uncertain spacecraft attitude control subsystem simulator. The reaction wheels' angular momentum and their rate saturation are concerned in the controller design. The super twisting algorithm (STA) is devised in a way to make the reaction wheels into rest at the end of the maneuver. A nonlinear‐disturbance‐observer (NDO) is applied in estimating the external disturbances, unmodeled inertia moment, the eccentricity of rotation and mass center of simulator, and the reaction wheel saturation constraint. The finite‐time stability of the closed‐loop system is established according to the Lyapunov theory. The simulation and experimental results of this newly designed controller‐observer on the spacecraft attitude simulator are compared in uncertain conditions.

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Section: Simulation and Experimental Resultsmentioning

confidence: 99%

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…The reaction wheels are used as control actuator. The total angular spacecraft simulator is the sum of angular momentum of the platform and the actuators expressed as (1) [10,11]:…”

Section: Spacecraft Simulator Dynamic Equationmentioning

confidence: 99%

“…The reaction wheels are used as control actuator. The total angular spacecraft simulator is the sum of angular momentum of the platform and the actuators expressed as () [10, 11]:

{boldh}_{t} = boldJ boldω + {boldh}_{w},

where

boldJ, bold-italicω

, and h w are the platform inertia matrix, angular velocity vector, and angular momentum of reaction wheels, respectively. By applying the Euler dynamic equation in the body coordinate, () is yield:

{bold-italicτ}_{d} = {\overset{boldh}{true}}_{t} + boldω \times {boldh}_{t},

where

{bold-italicτ}_{d}

is the total disturbance torque acting on the simulator, expressed through ():

{bold-italicτ}_{d} bold= {boldd}_{0} + m g ((), {boldr}_{s} \times boldk),

where

{boldr}_{s} = ([], \begin{matrix} center center center \\ array r_{x} & array r_{y} & array r_{z} \end{matrix})

and k and d 0 are a position vector from the platform rotation center to its mass‐center, a unit vector in the direction of gravity and unmodeled disturbances, respectively.…”

Section: Spacecraft Simulator Dynamic Equationmentioning

confidence: 99%

See 2 more Smart Citations

Finite‐time control of spacecraft and hardware in the loop tuning

Ali

Malekzadeh

Ataei

2022

Asian Journal of Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…It could be extended to the case of both external disturbance and inertial matrix uncertainty in [12]. Aiming at the problem that the angular velocities of multiple spacecraft cannot be measured, the literature [13] gives a scheme of coordinated attitude tracking control. Reference [14] proposed a neural network control scheme to solve the distributed attitude synchronization control problem of multiple satellite formations in the presence of input saturation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive terminal sliding mode control for satellite formation flying system with external disturbance and actuator misalignment

Gao

Shan

2021

Int. J. Dynam. Control

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In this paper, the distributed attitude synchronization control problem is addressed for satellite formation flying system (SFFS) with external disturbance and actuator misalignment by using adaptive terminal sliding mode control (ATSMC) technique. The satellite attitude system model considered in this paper is transformed into a lagrange nonlinear system. On this basis, a terminal sliding mode surface is designed for the attitude tracking error of SFFS, then a novel adaptive terminal sliding mode control scheme base on neural networks is developed, such that the satisfactory formation flying performance could be achieved in existence of external disturbance. Meanwhile, the obtained ATSMC scheme are extended to the actuator misalignment case, and Lyapunov stability theory is used to prove the stability and synchronization of the whole closed loop SFFS. The simulation results are given to demonstrate the effectiveness and superiority of the proposed control strategy.

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Method and Implementation of Vehicle Body Attitude Detection Based on Beidou Satellite

Wang

2023

Lecture Notes on Data Engineering and Communications Technologies

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Attitude control of spacecraft simulator without angular velocity measurement

Cited by 19 publications

References 24 publications

Finite‐time control of spacecraft and hardware in the loop tuning

Finite‐time control of spacecraft and hardware in the loop tuning

Adaptive terminal sliding mode control for satellite formation flying system with external disturbance and actuator misalignment

Method and Implementation of Vehicle Body Attitude Detection Based on Beidou Satellite

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