Optimal control of nonlinear partially-unknown systems with
unsymmetrical input constraints and its applications to the optimal UAV
circumnavigation problem
Aimed at solving the optimal control problem for nonlinear systems with
unsymmetrical input constraints, we present an online adaptive approach for
partially unknown control systems/dynamics. The designed algorithm converges
online to the optimal control solution without the knowledge of the internal
system dynamics. The optimality of the obtained control policy and the
stability for the closed-loop dynamic optimality are proved theoretically. The
proposed method greatly relaxes the assumption on the form of the internal
dynamics and input constraints in previous works. Besides, the control design
framework proposed in this paper offers a new approach to solve the optimal
circumnavigation problem involving a moving target for a fixed-wing unmanned
aerial vehicle (UAV). The control performance of our method is compared with
that of the existing circumnavigation control law in a numerical simulation and
the simulation results validate the effectiveness of our algorithm