2021
DOI: 10.1016/j.ejcon.2021.06.021
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Energy optimal attitude control for a solar-powered spacecraft

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Cited by 14 publications
(22 citation statements)
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“…The functions f (•) and g(•) are designed to steer ω b ob and q o b , respectively, to their desired final states. More specifically, [20].…”
Section: B Maximum Hands-off Controllermentioning
confidence: 99%
See 1 more Smart Citation
“…The functions f (•) and g(•) are designed to steer ω b ob and q o b , respectively, to their desired final states. More specifically, [20].…”
Section: B Maximum Hands-off Controllermentioning
confidence: 99%
“…The NLP-solver IPOPT was used to solve the optimization problems, using the solver's default options. The optimal control problems in (17), (19) and (20) were discretized using direct multiple-shooting, whereas the dynamics of the spacecraft were discretized using Runge-Kutta 4 integration. The output from the PD controller was used as the initial guesses for the L 1 -optimal controller, and the output from the L 1 -optimal controller was given as initial guesses for the maximum hands-off controller and the moving maximum hands-off controller.…”
Section: Simulation Setupmentioning
confidence: 99%
“…An example can be found in reference [7] which develops a technique to prevent sudden uncontrolled maneuvers while keeping the nadir pointing direction. Other authors such as Kristiansen and Gravdahl [8] have focused on the net power gain of solar panels. In their work, they propose a balance between the power generated by the panels and the additional energy consumption by the attitude control subsystem required to maintain the optimal Sun-tracking attitude.…”
Section: Introductionmentioning
confidence: 99%
“…In [16], a switch geometrical method control scheme is derived for energy-optimal reorientation under input saturation. Addressing the power limitation of CubeSat, a constrained optimal attitude control problem can be solved aiding by the IPOPT solver [17]. It can be noted that the above-considered constraints are static, and numerical optimization algorithms are still awkward to cope with them while satisfying real-time computation, not to mention the guarantee of prescribed performance (a dynamical system behavioral bound).…”
Section: Introductionmentioning
confidence: 99%