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Optimal and autonomous control using reinforcement learning: A survey
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 …
feedback control solutions to optimal regulation and tracking of single and multiagent …
Learning-based control: A tutorial and some recent results
This monograph presents a new framework for learning-based control synthesis of
continuous-time dynamical systems with unknown dynamics. The new design paradigm …
continuous-time dynamical systems with unknown dynamics. The new design paradigm …
Model-Free λ-Policy Iteration for Discrete-Time Linear Quadratic Regulation
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 …
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 …
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
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 …
systems with completely unknown dynamics. A general bounded L 2-gain tracking problem …
Adaptive dynamic programming and adaptive optimal output regulation of linear systems
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 …
systems, which aims to achieve asymptotic tracking and disturbance rejection by minimizing …
Hamiltonian-driven adaptive dynamic programming with approximation errors
In this article, we consider an iterative adaptive dynamic programming (ADP) algorithm
within the Hamiltonian-driven framework to solve the Hamilton–Jacobi–Bellman (HJB) …
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
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 …
design for linear continuous-time systems with completely unknown dynamics. Inspired by …
Event-triggered optimal control with performance guarantees using adaptive dynamic programming
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 …
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
This paper studies the adaptive and optimal output-feedback problem for continuous-time
uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback …
uncertain systems with nonlinear dynamic uncertainties. Data-driven output-feedback …