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Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle
An unmanned surface vehicle (USV) under complicated marine environments can hardly be
modeled well such that model-based optimal control approaches become infeasible. In this …
modeled well such that model-based optimal control approaches become infeasible. In this …
Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle
In this article, a novel reinforcement learning-based optimal tracking control (RLOTC)
scheme is established for an unmanned surface vehicle (USV) in the presence of complex …
scheme is established for an unmanned surface vehicle (USV) in the presence of complex …
Observer-based adaptive fuzzy decentralized optimal control design for strict-feedback nonlinear large-scale systems
In this paper, the problem of adaptive fuzzy decentralized optimal control is investigated for a
class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear …
class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear …
Event-triggered fault-tolerant control for input-constrained nonlinear systems with mismatched disturbances via adaptive dynamic programming
In this paper, the issue of event-triggered optimal fault-tolerant control is investigated for
input-constrained nonlinear systems with mismatched disturbances. To eliminate the effect …
input-constrained nonlinear systems with mismatched disturbances. To eliminate the effect …
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 …
Neural network control-based adaptive learning design for nonlinear systems with full-state constraints
In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state
constraints, an adaptive neural network control method is investigated in this paper. The …
constraints, an adaptive neural network control method is investigated in this paper. The …
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 …
Optimized backstep** for tracking control of strict-feedback systems
In this paper, a control technique named optimized backstep** is first proposed by
implementing tracking control for a class of strict-feedback systems, which considers …
implementing tracking control for a class of strict-feedback systems, which considers …
Air-breathing hypersonic vehicle tracking control based on adaptive dynamic programming
In this paper, we propose a data-driven supplementary control approach with adaptive
learning capability for air-breathing hypersonic vehicle tracking control based on action …
learning capability for air-breathing hypersonic vehicle tracking control based on action …
Improved sliding mode design for load frequency control of power system integrated an adaptive learning strategy
Randomness from the power load demand and renewable generations causes frequency
oscillations among interconnected power systems. Due to the requirement of synchronism of …
oscillations among interconnected power systems. Due to the requirement of synchronism of …