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

Industrial information integration engineering (IIIE) is a set of foundational concepts and
techniques that facilitate the industrial information integration process. In recent years, many …

The adaptive dynamic programming (ADP) technology has been widely used benefiting
from its recursive structure in forward and the prospective conception of reinforcement …

This paper presents an event-triggered adaptive dynamic programming (ETADP) algorithm
to study the optimal decentralized control issue of interconnected nonlinear systems subject …

Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and
provides the evolution of the system state in real-time. This paper focuses on the control and …

The heuristic dynamic programming (HDP)()-based optimal control strategy, which takes a
long-term prediction parameter into account using an iterative manner, accelerates the …

In this article, a novel distributed policy iteration algorithm is established for infinite horizon
optimal control problems of continuous-time nonlinear systems. In each iteration of the …

This article investigates the attitude control problem for a novel foldable wave-energy
powered autonomous underwater vehicle (FWEPAUV) with model uncertainties and …

This paper investigates the dynamic event-triggered fault-tolerant optimal control strategy for
a class of output feedback nonlinear discrete-time systems subject to actuator faults and …

In this article, a new deep reinforcement learning (RL) method, called asynchronous
advantage actor-critic (A3C) method, is developed to solve the optimal control problem of …