Event-triggered optimal neuro-controller design with reinforcement learning for unknown nonlinear systems
This paper develops an optimal control scheme for continuous-time unknown nonlinear
systems using the event-triggering mechanism. Different from designing controllers using …
systems using the event-triggering mechanism. Different from designing controllers using …
Model-free adaptive dynamic programming based near-optimal decentralized tracking control of reconfigurable manipulators
B Zhao, Y Li - International Journal of Control, Automation and …, 2018 - Springer
In this paper, a model-free near-optimal decentralized tracking control (DTC) scheme is
developed for reconfigurable manipulators via adaptive dynamic programming algorithm …
developed for reconfigurable manipulators via adaptive dynamic programming algorithm …
Three-dimensional path tracking control of autonomous underwater vehicle based on deep reinforcement learning
Y Sun, C Zhang, G Zhang, H Xu, X Ran - Journal of Marine Science and …, 2019 - mdpi.com
In this paper, the three-dimensional (3D) path tracking control of an autonomous underwater
vehicle (AUV) under the action of sea currents was researched. A novel reward function was …
vehicle (AUV) under the action of sea currents was researched. A novel reward function was …
Approximate dynamic programming for two-player zero-sum game related to H ∞ control of unknown nonlinear continuous-time systems
This paper develops a concurrent learning-based approximate dynamic programming (ADP)
algorithm for solving the two-player zero-sum (ZS) game arising in H∞ control of continuous …
algorithm for solving the two-player zero-sum (ZS) game arising in H∞ control of continuous …
Full-state neural network observer-based hybrid quantum diagonal recurrent neural network adaptive tracking control
This study introduces a neural network (NN) adaptive tracking controller-based
reinforcement learning (RL) scheme for unknown nonlinear systems. First, an observer …
reinforcement learning (RL) scheme for unknown nonlinear systems. First, an observer …
Adaptive output feedback force tracking control for Lower Extremity Power-assisted Exoskeleton
S Song, Y Cao, H Wang, J Xue, X Zhang… - Journal of control …, 2018 - ceai.srait.ro
This paper presents an output feedback adaptive force tracking control scheme for Lower
Extremity Power-assisted Exoskeleton (LEPEX). LEPEX is driven by electro-hydraulic …
Extremity Power-assisted Exoskeleton (LEPEX). LEPEX is driven by electro-hydraulic …
Smart grid optimized operation driven by reinforcement learning
P Fisco Compte - 2022 - upcommons.upc.edu
This thesis focuses on the development of a reinforcement learning model for the operation
and demand response control of a smart grid. First, a generic problem is formulated to define …
and demand response control of a smart grid. First, a generic problem is formulated to define …
Extended nonlinear observer canonical form depending on system output and auxiliary state
H Cho, J Yang, JH Seo - International Journal of Control, Automation and …, 2015 - Springer
This paper deals with the problem of transforming a single output nonlinear system with an
auxiliary dynamics into an extended nonlinear observer canonical form (ENOCF). The …
auxiliary dynamics into an extended nonlinear observer canonical form (ENOCF). The …
[PDF][PDF] DC Motor Speed Control System in the Design and Implementation of the Smart Car
W KONG, K YAO, D DONG, W ZHANG, K YAN - scholar.archive.org
In the DC motor speed control system based on MK100N512ZLL10 micro controller, the duty
cycle of DC motor depends on the micro controller module FTM PWM output, thereby control …
cycle of DC motor depends on the micro controller module FTM PWM output, thereby control …