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

This paper provides an overview of the reinforcement learning and optimal adaptive control
literature and its application to robotics. Reinforcement learning is bridging the gap between …

The distributed tracking problem for uncertain nonlinear multiagent systems (MASs) under
event-triggered communication is an important issue. However, existing results provide …

Many previous works of soft wearable exoskeletons (exosuit) target at improving the human
locomotion assistance, without considering the impedance adaption to interact with the …

In this article, we investigate the distributed resilient observer-based fault-tolerant control
problem for heterogeneous linear multiagent systems in the presence of actuator faults and …

This paper deals with the design of an H∞ tracking controller for nonlinear continuous-time
systems with completely unknown dynamics. A general bounded L 2-gain tracking problem …

Motivated by the desire to extend the well‐known robust integral of the sign of the error
(RISE) feedback control to handle both matched and mismatched disturbances …

Reinforcement learning (RL) has been successfully employed as a powerful tool in
designing adaptive optimal controllers. Recently, off-policy learning has emerged to design …

In this article, we consider the distributed fault-tolerant resilient consensus problem for
heterogeneous multiagent systems (MASs) under both physical failures and network denial …

This paper presents three design techniques for cooperative control of multiagent systems
on directed graphs, namely, Lyapunov design, neural adaptive design, and linear quadratic …