Optimal and autonomous control using reinforcement learning: A survey

B Kiumarsi, KG Vamvoudakis… - IEEE transactions on …, 2017‏ - ieeexplore.ieee.org
This paper reviews the current state of the art on reinforcement learning (RL)-based
feedback control solutions to optimal regulation and tracking of single and multiagent …

Learning-based control: A tutorial and some recent results

ZP Jiang, T Bian, W Gao - Foundations and Trends® in …, 2020‏ - nowpublishers.com
This monograph presents a new framework for learning-based control synthesis of
continuous-time dynamical systems with unknown dynamics. The new design paradigm …

Model-Free λ-Policy Iteration for Discrete-Time Linear Quadratic Regulation

Y Yang, B Kiumarsi, H Modares… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
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 …

Observer-based adaptive fuzzy fault-tolerant optimal control for SISO nonlinear systems

Y Li, K Sun, S Tong - IEEE transactions on cybernetics, 2018‏ - ieeexplore.ieee.org
This paper investigates adaptive fuzzy output feedback fault-tolerant optimal control problem
for a class of single-input and single-output nonlinear systems in strict feedback form. The …

Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning

H Modares, FL Lewis, ZP Jiang - IEEE transactions on neural …, 2015‏ - ieeexplore.ieee.org
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 …

Adaptive dynamic programming and adaptive optimal output regulation of linear systems

W Gao, ZP Jiang - IEEE Transactions on Automatic Control, 2016‏ - ieeexplore.ieee.org
This note studies the adaptive optimal output regulation problem for continuous-time linear
systems, which aims to achieve asymptotic tracking and disturbance rejection by minimizing …

Hamiltonian-driven adaptive dynamic programming with approximation errors

Y Yang, H Modares, KG Vamvoudakis… - IEEE Transactions …, 2021‏ - ieeexplore.ieee.org
In this article, we consider an iterative adaptive dynamic programming (ADP) algorithm
within the Hamiltonian-driven framework to solve the Hamilton–Jacobi–Bellman (HJB) …

Value iteration and adaptive dynamic programming for data-driven adaptive optimal control design

T Bian, ZP Jiang - Automatica, 2016‏ - Elsevier
This paper presents a novel non-model-based, data-driven adaptive optimal controller
design for linear continuous-time systems with completely unknown dynamics. Inspired by …

Event-triggered optimal control with performance guarantees using adaptive dynamic programming

B Luo, Y Yang, D Liu, HN Wu - IEEE transactions on neural …, 2019‏ - ieeexplore.ieee.org
This paper studies the problem of event-triggered optimal control (ETOC) for continuous-
time nonlinear systems and proposes a novel event-triggering condition that enables …

Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming

W Gao, Y Jiang, ZP Jiang, T Chai - Automatica, 2016‏ - Elsevier
This paper studies the adaptive and optimal output-feedback problem for continuous-time
uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback …