Port-Hamiltonian systems in adaptive and learning control: A survey
Port-Hamiltonian (PH) theory is a novel, but well established modeling framework for
nonlinear physical systems. Due to the emphasis on the physical structure and modular …
nonlinear physical systems. Due to the emphasis on the physical structure and modular …
Adaptive neural network tracking control for underactuated systems with matched and mismatched disturbances
This paper studies neural network-based tracking control of underactuated systems with
unknown parameters and with matched and mismatched disturbances. Novel adaptive …
unknown parameters and with matched and mismatched disturbances. Novel adaptive …
[HTML][HTML] Q-Learning-based model predictive variable impedance control for physical human-robot collaboration
Physical human-robot collaboration is increasingly required in many contexts (such as
industrial and rehabilitation applications). The robot needs to interact with the human to …
industrial and rehabilitation applications). The robot needs to interact with the human to …
[BOEK][B] Motion control of underactuated mechanical systems
J Moreno-Valenzuela, C Aguilar-Avelar - 2018 - Springer
The growth in automated manufacturing since the '60s has motivated the study of the control
and motion planning of many types of mechanical systems, such as industrial manipulators …
and motion planning of many types of mechanical systems, such as industrial manipulators …
An overview on recent machine learning techniques for Port Hamiltonian systems
K Cherifi - Physica D: Nonlinear Phenomena, 2020 - Elsevier
Port Hamiltonian systems have grown in interest in recent years due to their modular
property, close relation with physical modelling and the interesting properties arising from …
property, close relation with physical modelling and the interesting properties arising from …
Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach
Large-scale cyber-physical systems require that control policies are distributed, that is, that
they only rely on local real-time measurements and communication with neighboring agents …
they only rely on local real-time measurements and communication with neighboring agents …
A fast sampling method for estimating the domain of attraction
Most stabilizing controllers designed for nonlinear systems are valid only within a specific
region of the state space, called the domain of attraction (DoA). Computation of the DoA is …
region of the state space, called the domain of attraction (DoA). Computation of the DoA is …
Adaptive neural network control for the trajectory tracking of the Furuta pendulum
The purpose of this paper is to introduce a novel adaptive neural network-based control
scheme for the Furuta pendulum, which is a two degree-of-freedom underactuated system …
scheme for the Furuta pendulum, which is a two degree-of-freedom underactuated system …
Machine Learning in Computer Aided Engineering
The extraordinary success of Machine Learning (ML) in many complex heuristic fields has
promoted its introduction in more analytical engineering fields, improving or substituting …
promoted its introduction in more analytical engineering fields, improving or substituting …
Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system
Energy system optimization is important in strengthening stability, reliability and economy,
which is usually given by static linear or nonlinear programming. However, the challenge …
which is usually given by static linear or nonlinear programming. However, the challenge …