학술논문

Symbolic Optimal Control
Document Type
Periodical
Source
IEEE Transactions on Automatic Control IEEE Trans. Automat. Contr. Automatic Control, IEEE Transactions on. 64(6):2224-2239 Jun, 2019
Subject
Signal Processing and Analysis
Optimal control
Adaptive control
Convergence
Upper bound
Perturbation methods
Aerospace electronics
Approximate dynamic programming
difference inclusion
discrete abstraction
nonlinear system
optimal control
symbolic control
Language
ISSN
0018-9286
1558-2523
2334-3303
Abstract
We present novel results on the solution of a class of leavable, undiscounted optimal control problems in the minimax sense for nonlinear, continuous-state, discrete-time plants. The problem class includes entry-(exit-)time problems as well as minimum-time, pursuit-evasion, and reach-avoid games as special cases. We utilize auxiliary optimal control problems (“abstractions”) to compute both upper bounds of the value function, i.e., of the achievable closed-loop performance, and symbolic feedback controllers realizing those bounds. The abstractions are obtained from discretizing the problem data, and we prove that the computed bounds and the performance of the symbolic controllers converge to the value function as the discretization parameters approach zero. In particular, if the optimal control problem is solvable on some compact subset of the state space, and if the discretization parameters are sufficiently small, then we obtain a symbolic feedback controller solving the problem on that subset. These results do not assume the continuity of the value function or any problem data, and they fully apply in the presence of hard state and control constraints.