This paper is concerned with devising nonlinear optimal guidance for intercepting a stationary target with a desired impact time. According to Pontryagin’s maximum principle, some optimality conditions for the solutions of the nonlinear optimal interception problem are established; and the structure of the corresponding optimal control is presented. By employing the optimality conditions, we formulate a parameterized system so that its solution space is the same as that of the nonlinear optimal interception problem. As a consequence, a simple propagation of the parameterized system, without using any optimization method, is sufficient to generate enough sampled data for the mapping from the current state and time-to-go to the optimal guidance command. By virtue of the universal approximation theorem, a feedforward neural network, trained by the generated data, is able to represent the mapping from the current state and time-to-go to the optimal guidance command. Therefore, the trained network eventually can generate impact-time-constrained nonlinear optimal guidance within a constant time. Finally, the developed nonlinear optimal guidance is exemplified and studied through simulations, showing that the nonlinear optimal guidance law performs better than existing interception guidance laws.
Nonlinear Optimal Guidance for Intercepting Stationary Targets with Impact-Time Constraints
Journal of Guidance, Control, and Dynamics ; 45 , 9 ; 1614-1626
2022-05-27
13 pages
Article (Journal)
Electronic Resource
English
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