Solving Constrained Optimal Control Problems Using State-Dependent Factorization and Chebyshev Polynomials

2018-03-01
Gomroki, Mohammad Mehdi
Topputo, Francesco
Bernelli-Zazzera, Franco
Tekinalp, Ozan
The present work introduces a method to solve constrained nonlinear optimal control problems using state-dependent coefficient factorization and Chebyshev polynomials. A recursive approximation technique known as approximating sequence of Riccati equations is used to replace the nonlinear problem by a sequence of linear-quadratic and time-varying approximating problems. The state variables are approximated and expanded in Chebyshev polynomials. Then, the control variables are written as a function of state variables and their derivatives. The constrained nonlinear optimal control problem is then converted to quadratic programming problem, and a constrained optimization problem is solved. Different final state conditions (unspecified, partly specified, and fully specified) are handled, and the effectiveness of the proposed method is demonstrated by solving sample problems.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS

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Citation Formats
M. M. Gomroki, F. Topputo, F. Bernelli-Zazzera, and O. Tekinalp, “Solving Constrained Optimal Control Problems Using State-Dependent Factorization and Chebyshev Polynomials,” JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, pp. 618–631, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46647.