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

This monograph presents a new framework for learning-based control synthesis of
continuous-time dynamical systems with unknown dynamics. The new design paradigm …

The cooperative output regulation problem (CORP) is an extension of the leader-following
consensus problem of multi-agent systems (MASs), and has been studied by two …

In this paper, we investigate the learning-based adaptive optimal output regulation problem
with convergence rate requirement for disturbed linear continuous-time systems. An …

This article addresses the resilient practical cooperative output regulation problem
(RPCORP) for multiagent systems subjected to both denial-of-service (DoS) attacks and …

In this paper, to eliminate the tracking error by using adaptive dynamic programming (ADP)
algorithms, a novel formulation of the value function is presented for the optimal tracking …

An adaptive decentralized asymptotic tracking control scheme is developed in this paper for
a class of large-scale nonlinear systems with unknown strong interconnections, unknown …

In this paper, we consider the problem of output regulation in heterogeneous networked
systems. In order to cooperatively achieve the global objective, each agent is required to …

This paper studies a cooperative adaptive optimal output regulation problem for a class of
strict-feedback nonlinear discrete-time (DT) multi-agent systems (MASs) with partially …

This paper proposes a novel control approach to solve the cooperative H∞ output
regulation problem for linear continuous-time multi-agent systems (MASs). Different from …