Observed-based adaptive fuzzy decentralized tracking control for switched uncertain nonlinear large-scale systems with dead zones
S Tong, L Zhang, Y Li - IEEE Transactions on Systems, Man …, 2015 - ieeexplore.ieee.org
In this paper, the problem of adaptive fuzzy decentralized output-feedback control design is
investigated for a class of switched nonlinear large-scale systems in strict-feedback form …
investigated for a class of switched nonlinear large-scale systems in strict-feedback form …
An overview on bipedal gait control methods
C Hu, S Xie, L Gao, S Lu, J Li - IET Collaborative Intelligent …, 2023 - Wiley Online Library
Bipedal gait control has always been a very challenging issue due to the multi‐joint and non‐
linear structure of humanoid robots and frequent robot–environment interactions. To realise …
linear structure of humanoid robots and frequent robot–environment interactions. To realise …
Constrained multilegged robot system modeling and fuzzy control with uncertain kinematics and dynamics incorporating foot force optimization
This paper studies the optimal distribution of feet forces and control of multilegged robots
with uncertainties in both kinematics and dynamics. First, a constrained dynamics for …
with uncertainties in both kinematics and dynamics. First, a constrained dynamics for …
A wireless BCI and BMI system for wearable robots
W He, Y Zhao, H Tang, C Sun… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
To increase the performance of a brain-computer interface and brain-machine interface
system, we propose some methods and algorithms for electroencephalograph (EEG) signal …
system, we propose some methods and algorithms for electroencephalograph (EEG) signal …
Self-learning physical reservoir computer
A self-learning physical reservoir computer is demonstrated using an adaptive oscillator.
Whereas physical reservoir computing repurposes the dynamics of a physical system for …
Whereas physical reservoir computing repurposes the dynamics of a physical system for …
Designing spontaneous behavioral switching via chaotic itinerancy
K Inoue, K Nakajima, Y Kuniyoshi - Science advances, 2020 - science.org
Chaotic itinerancy is a frequently observed phenomenon in high-dimensional nonlinear
dynamical systems and is characterized by itinerant transitions among multiple quasi …
dynamical systems and is characterized by itinerant transitions among multiple quasi …
Development of a new robust stable walking algorithm for a humanoid robot using deep reinforcement learning with multi-sensor data fusion
The difficult task of creating reliable mobility for humanoid robots has been studied for
decades. Even though several different walking strategies have been put forth and walking …
decades. Even though several different walking strategies have been put forth and walking …
Robust biped locomotion using deep reinforcement learning on top of an analytical control approach
This paper proposes a modular framework to generate robust biped locomotion using a tight
coupling between an analytical walking approach and deep reinforcement learning. This …
coupling between an analytical walking approach and deep reinforcement learning. This …
Biologically inspired control system for 3-D locomotion of a humanoid biped robot
This paper proposes the control system for 3-D locomotion of a humanoid biped robot based
on a biological approach. The muscular system in the human body and the neural oscillator …
on a biological approach. The muscular system in the human body and the neural oscillator …
Robust decentralized formation tracking control for stochastic large-scale biped robot team system under external disturbance and communication requirements
BS Chen, YY Tsai, MY Lee - IEEE transactions on control of …, 2021 - ieeexplore.ieee.org
In this study, a robust decentralized stochastic H∞ tracking control design is proposed to
deal with the team formation tracking problem for a large-scale biped robot team system with …
deal with the team formation tracking problem for a large-scale biped robot team system with …