Observer-based neuro-adaptive optimized control of strict-feedback nonlinear systems with state constraints
Y Li, Y Liu, S Tong - IEEE Transactions on Neural Networks and …, 2021 - ieeexplore.ieee.org
This article proposes an adaptive neural network (NN) output feedback optimized control
design for a class of strict-feedback nonlinear systems that contain unknown internal …
design for a class of strict-feedback nonlinear systems that contain unknown internal …
Adaptive-critic design for decentralized event-triggered control of constrained nonlinear interconnected systems within an identifier-critic framework
This article studies the decentralized event-triggered control problem for a class of
constrained nonlinear interconnected systems. By assigning a specific cost function for each …
constrained nonlinear interconnected systems. By assigning a specific cost function for each …
Observer-based adaptive optimized control for stochastic nonlinear systems with input and state constraints
Y Li, J Zhang, W Liu, S Tong - IEEE transactions on neural …, 2021 - ieeexplore.ieee.org
In this work, an adaptive neural network (NN) optimized output-feedback control problem is
studied for a class of stochastic nonlinear systems with unknown nonlinear dynamics, input …
studied for a class of stochastic nonlinear systems with unknown nonlinear dynamics, input …
Adaptive fuzzy inverse optimal control for uncertain strict-feedback nonlinear systems
Y Li, X Min, S Tong - IEEE Transactions on Fuzzy Systems, 2019 - ieeexplore.ieee.org
This article first investigates the adaptive fuzzy inverse optimal control design problem for a
class of uncertain strict-feedback nonlinear systems. Fuzzy logic systems are utilized to …
class of uncertain strict-feedback nonlinear systems. Fuzzy logic systems are utilized to …
Adaptive critic nonlinear robust control: A survey
Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each
other when performing intelligent optimization. They are both regarded as promising …
other when performing intelligent optimization. They are both regarded as promising …
Data-driven optimal consensus control for discrete-time multi-agent systems with unknown dynamics using reinforcement learning method
This paper investigates the optimal consensus control problem for discrete-time multi-agent
systems with completely unknown dynamics by utilizing a data-driven reinforcement …
systems with completely unknown dynamics by utilizing a data-driven reinforcement …
Comprehensive comparison of online ADP algorithms for continuous-time optimal control
Online learning is an important property of adaptive dynamic programming (ADP). Online
observations contain plentiful dynamics information, and ADP algorithms can utilize them to …
observations contain plentiful dynamics information, and ADP algorithms can utilize them to …
A multistage game in smart grid security: A reinforcement learning solution
Existing smart grid security research investigates different attack techniques and cascading
failures from the attackers' viewpoints, while the defenders' or the operators' protection …
failures from the attackers' viewpoints, while the defenders' or the operators' protection …
Fuzzy approximation-based adaptive backstepping optimal control for a class of nonlinear discrete-time systems with dead-zone
YJ Liu, Y Gao, S Tong, Y Li - IEEE Transactions on Fuzzy …, 2015 - ieeexplore.ieee.org
In this paper, an adaptive fuzzy optimal control design is addressed for a class of unknown
nonlinear discrete-time systems. The controlled systems are in a strict-feedback frame and …
nonlinear discrete-time systems. The controlled systems are in a strict-feedback frame and …
Reinforcement-learning-based robust controller design for continuous-time uncertain nonlinear systems subject to input constraints
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 challenging problem. The constrained-input coupled with the inability to identify accurately …