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 …

Reinforcement learning (RL) has roots in dynamic programming and it is called
adaptive/approximate dynamic programming (ADP) within the control community. This paper …

The core task of tracking control is to make the controlled plant track a desired trajectory. The
traditional performance index used in previous studies cannot eliminate completely the …

This article investigates the model-free fault-tolerant containment control problem for
multiagent systems (MASs) with time-varying actuator faults. Depending on the relative state …

This article presents a model-free-policy iteration (-PI) for the discrete-time linear quadratic
regulation (LQR) problem. To solve the algebraic Riccati equation arising from solving the …

This article investigates a neural network (NN)‐based control problem for unknown discrete‐
time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event …

With the rapid development in information science and technology, many businesses and
industries have undergone great changes, such as chemical industry, electric power …

In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state
constraints, an adaptive neural network control method is investigated in this paper. The …

Optimal control problems are ubiquitous in practical engineering applications and social life
with the idea of cost or resource conservation. Based on the critic learning scheme, adaptive …

In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed
to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear …