This article reviews the recent development of adaptive dynamic programming (ADP) with
applications in control. First, its applications in optimal regulation are introduced, and some …

In this paper, we present an overview of adaptive control by contrasting model‐based
approaches with data‐driven approaches. Indeed, we propose to classify adaptive …

In this paper, a new formulation for the optimal tracking control problem (OTCP) of
continuous-time nonlinear systems is presented. This formulation extends the integral …

In this paper, an integral reinforcement learning (IRL) algorithm on an actor–critic structure is
developed to learn online the solution to the Hamilton–Jacobi–Bellman equation for partially …

This note proposes a novel data-driven solution to the cooperative adaptive optimal control
problem of leader-follower multiagent systems under switching network topology. The …

An optimal control method is developed for unknown continuous-time systems with unknown
disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented …

This article presents an event-sampled integral reinforcement learning algorithm for partially
unknown nonlinear systems using a novel dynamic event-triggering strategy. This is a novel …

This paper develops a novel adaptive integral sliding-mode control (SMC) technique to
improve the tracking performance of a wheeled inverted pendulum (WIP) system, which …

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL
(I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine …

In the inverse reinforcement learning (RL) problem, there are two agents. A learner agent
seeks to mimic another expert agent's state and control input behavior trajectories by …