In this paper, a novel approach based on the Q-learning algorithm is proposed to solve the infinite-horizon

linear quadratic tracker (LQT) for unknown discrete-time systems in a causal manner. It is assumed

that ...

of policy iteration and optimal adaptive control techniques to solve the leader follower consensus problem under known and unknown dynamics. Simulation results verify the effectiveness of the proposed methods....

optimal control solution are obtained simultaneously by solving

the augmented ARE. To find the solution to the augmented

ARE online, policy iteration as a class of reinforcement learning

algorithms, is employed. This algorithm is implemented...

nonquadratic

performance functional. An online policy iteration algorithm that uses integral

reinforcement knowledge is developed to learn the solution to the optimal control problem

online without knowing the full dynamics model...

In this paper, an online adaptive optimal control algorithm based on policy iteration (PI) is developed to solve the H∞ control problem of partially unknown nonlinear continuous-time (CT) systems. The convergence of existing PI algorithms...

This paper is an effort towards developing an online learning algorithm to find the optimal control

solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on

the policy iteration (PI...