This paper studies the infinite-horizon adaptive optimal control of continuous-time linear
periodic (CTLP) systems, using reinforcement learning techniques. By means of policy …

This article studies the infinite-horizon adaptive optimal control of continuous-time linear
periodic (CTLP) systems. A novel value iteration (VI) based off-policy adaptive dynamic …

An identification-free control design strategy for discrete-time linear time-varying systems
with unknown dynamics is introduced. The closed-loop system (under state feedback) is …

Considering discrete-time linear time-varying systems with unknown dynamics, controllers
guaranteeing bounded closed-loop trajectories, optimal performance, and robustness to …

This paper studies data-driven learning-based methods for the finite-horizon optimal control
of linear time-varying discrete-time systems. First, a novel finite-horizon Policy Iteration (PI) …

We solve the problem of two-point boundary optimal control of linear time-varying systems
with unknown model dynamics using reinforcement learning. Leveraging singular …

This paper presents a data-driven method to obtain an approximate solution of the finite-
horizon optimal control problem for linear time-varying discrete-time systems. Firstly, a finite …

In order to establish the dynamic equations of the rigid-flexible coupled robotic mechanisms
with large beam-deformations over the horizontal plane, a thorough modeling technique …

In this paper, we propose a novel dynamic programming (DP) algorithm, under the name of
hybrid iteration (HI), for continuous-time linear systems. The proposed HI approach …

In this paper, the optimal control problem for unknown continuous-time linear periodic
(CTLP) systems is investigated. A model-based bias-policy iteration algorithm for CTLP …