Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each
other when performing intelligent optimization. They are both regarded as promising …

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

This paper studies the robust optimal control design for a class of uncertain nonlinear
systems from a perspective of robust adaptive dynamic programming (RADP). The objective …

In this paper, the author focuses on establishing an intelligent critic control framework with
robustness guarantee for disturbed nonlinear systems. Combining the neural network …

This brief presents a novel framework of robust adaptive dynamic programming (robust-
ADP) aimed at computing globally stabilizing and suboptimal control policies in the …

In this paper, a novel robust adaptive dynamic programming (RADP)-based control strategy
is presented for the optimal control of a class of output-constrained continuous-time …

The design of stabilizing controller for uncertain nonlinear systems with control constraints is
a challenging problem. The constrained-input coupled with the inability to identify accurately …

A comprehensive look at state-of-the-art ADP theory and real-world applications This book
fills a gap in the literature by providing a theoretical framework for integrating techniques …

Although robust regulation problem has been well studied, solving robust tracking control
via online learning has not been fully solved, in particular for nonlinear systems. This paper …

This paper proposes a new approach to address robust control design for nonlinear
continuous-time systems with unmatched uncertainties. First, we transform the robust control …