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A symplectic pseudospectral method for nonlinear optimal control problems with inequality constraints

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Indexed by:期刊论文

Date of Publication:2017-05-01

Journal:ISA TRANSACTIONS

Included Journals:SCIE、EI、PubMed

Volume:68

Page Number:335-352

ISSN No.:0019-0578

Key Words:nonlinear optimal control; inequality constraints; quasilinearization; parametric variational principle; linear complementary problem

Abstract:A symplectic pseudospectral method based on the dual variational principle and the quasilinearization method is proposed and is successfully applied to solve nonlinear optimal control problems with inequality constraints in this paper. Nonlinear optimal control problem is firstly converted into a series of constraint linear-quadratic optimal control problems with the help of quasilinearization techniques. Then a symplectic pseudospectral method based on dual variational principle for solving the converted constrained linear-quadratic optimal control problems is developed. In the proposed method, inequality constraints which can be functions of pure state, pure control and mixed state-control are transformed into equality constraints with the help of parameteric variables. After that, state variables, costate variables and parametric variables are interpolated locally at Legendre-Gauss-Lobatto points. Finally, based on the parametric variational principle and complementary conditions, the converted problem is transformed into a standard linear complementary problem which can be solved easily. Numerical examples show that the proposed method is of high accuracy and efficiency. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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