State Parameterization Basic Spline Functions for Trajectory Optimization

Authors

  • Maha Musaddak Delphi Department of Applied Sciences | University of Technology | Baghdad | Iraq
  • Suha Najeeb Shihab Department of Applied Sciences | University of Technology | Baghdad | Iraq

DOI:

https://doi.org/10.26389/AJSRP.S270519

Keywords:

basic spline, Bernstein polynomials, state parameter algorithm, optimal control problems

Abstract

An important type of basic functions named basis spline (B-spline) is provided a simpler approximate and more stable approach to solve problems in optimal control. Furthermore, it can be proved that with special knot sequence, the B-spline basis are exactly Bernstein polynomials. The approximate technique is based on state variable is approximate as a linear combination of B-spline then anon linear optimization problem is obtained and the optimal coefficients are calculated using an iterative algorithm. Two different examples are tested using the proposed algorithm.

Author Biographies

  • Maha Musaddak Delphi, Department of Applied Sciences | University of Technology | Baghdad | Iraq

    Department of Applied Sciences | University of Technology | Baghdad | Iraq

  • Suha Najeeb Shihab, Department of Applied Sciences | University of Technology | Baghdad | Iraq

    Department of Applied Sciences | University of Technology | Baghdad | Iraq

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Published

2019-12-30

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How to Cite

Delphi, M. M., & Shihab, S. N. (2019). State Parameterization Basic Spline Functions for Trajectory Optimization. Journal of Natural Sciences, Life and Applied Sciences, 3(4), 119-110. https://doi.org/10.26389/AJSRP.S270519