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Low Thrust Minimum Time Orbit Transfer Nonlinear Optimization Using Impulse Discretization via the Modified Picard–Chebyshev Method

Darin Koblick1,2,3, Shujing Xu4, Joshua Fogel5, Praveen Shankar1

California State University - Long Beach, CA, USA.
Millennium Space Systems Inc., El Segundo, CA, USA.
Claremont Graduate University, CA, USA.
University of California - San Diego, CA, USA.
University of Southern California, Los Angeles, CA, USA.

Computer Modeling in Engineering & Sciences 2016, 111(1), 1-27. https://doi.org/10.3970/cmes.2016.111.001

Abstract

The Modified Picard-Chebyshev Method (MPCM) is implemented as an orbit propagation solver for a numerical optimization method that determines minimum time orbit transfer trajectory of a satellite using a series of multiple impulses at intermediate waypoints. The waypoints correspond to instantaneous impulses that are determined using a nonlinear constrained optimization routine, SNOPT with numerical force models for both Two-Body and J2 perturbations. It is found that using the MPCM increases run-time performance of the discretized lowthrust optimization method when compared to other sequential numerical solvers, such as Adams-Bashforth-Moulton and Gauss-Jackson 8th order methods.

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APA Style
Koblick, D., Xu, S., Fogel, J., Shankar, P. (2016). Low thrust minimum time orbit transfer nonlinear optimization using impulse discretization via the modified picard–chebyshev method. Computer Modeling in Engineering & Sciences, 111(1), 1-27. https://doi.org/10.3970/cmes.2016.111.001
Vancouver Style
Koblick D, Xu S, Fogel J, Shankar P. Low thrust minimum time orbit transfer nonlinear optimization using impulse discretization via the modified picard–chebyshev method. Comput Model Eng Sci. 2016;111(1):1-27 https://doi.org/10.3970/cmes.2016.111.001
IEEE Style
D. Koblick, S. Xu, J. Fogel, and P. Shankar "Low Thrust Minimum Time Orbit Transfer Nonlinear Optimization Using Impulse Discretization via the Modified Picard–Chebyshev Method," Comput. Model. Eng. Sci., vol. 111, no. 1, pp. 1-27. 2016. https://doi.org/10.3970/cmes.2016.111.001



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