The intelligent critic framework for advanced optimal control
The idea of optimization can be regarded as an important basis of many disciplines and
hence is extremely useful for a large number of research fields, particularly for artificial …
hence is extremely useful for a large number of research fields, particularly for artificial …
Hamiltonian-driven adaptive dynamic programming with efficient experience replay
This article presents a novel efficient experience-replay-based adaptive dynamic
programming (ADP) for the optimal control problem of a class of nonlinear dynamical …
programming (ADP) for the optimal control problem of a class of nonlinear dynamical …
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 …
Robust actor–critic learning for continuous-time nonlinear systems with unmodeled dynamics
This article considers the robust optimal control problem for a class of nonlinear systems in
the presence of unmodeled dynamics. An adaptive optimal controller is designed using the …
the presence of unmodeled dynamics. An adaptive optimal controller is designed using the …
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) …
Sampled-data consensus protocols for a class of second-order switched nonlinear multiagent systems
In this study, the sampled-data consensus problem is investigated for a class of
heterogeneous multiagent systems (MASs) in which each agent is described by a second …
heterogeneous multiagent systems (MASs) in which each agent is described by a second …
Reinforcement-learning-based tracking control of waste water treatment process under realistic system conditions and control performance requirements
The tracking control of a wastewater treatment process (WWTP) is considered. The process
is highly nonlinear, with strong coupling, difficult to model mathematically, and the operation …
is highly nonlinear, with strong coupling, difficult to model mathematically, and the operation …
Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics
J Zhong, T Wang, L Cheng - Complex & Intelligent Systems, 2021 - Springer
In actual welding scenarios, an effective path planner is needed to find a collision-free path
in the configuration space for the welding manipulator with obstacles around. However, as a …
in the configuration space for the welding manipulator with obstacles around. However, as a …
Safe reinforcement learning for dynamical games
This article presents a novel actor‐critic‐barrier structure for the multiplayer safety‐critical
systems. Non‐zero‐sum (NZS) games with full‐state constraints are first transformed into …
systems. Non‐zero‐sum (NZS) games with full‐state constraints are first transformed into …
Adaptive dynamic event-triggered bipartite time-varying output formation tracking problem of heterogeneous multiagent systems
This article investigates the bipartite time-varying output formation tracking problem of
heterogeneous linear multiagent systems with disturbances by adaptive dynamic event …
heterogeneous linear multiagent systems with disturbances by adaptive dynamic event …