216 citations · 542 across the 10 of their papers we have counts for
11 papers
Flexible Exoskeleton Control Based on Binding Alignment Strategy and Full-arm Coordination Mechanism
Chuang Cheng, Xinglong Zhang, Xieyuanli Chen +6
In rehabilitation, powered, and teleoperation exoskeletons, connecting the human body to the exoskeleton through binding attachments is a common configuration. However, the uncerta…
Learning-based Near-optimal Motion Planning for Intelligent Vehicles with Uncertain Dynamics
Yang Lu, Xinglong Zhang, Xin Xu +1
Motion planning has been an important research topic in achieving safe and flexible maneuvers for intelligent vehicles. However, it remains challenging to realize efficient and opt…
Model-Based Safe Reinforcement Learning with Time-Varying State and Control Constraints: An Application to Intelligent Vehicles
Xinglong Zhang, Yaoqian Peng, Biao Luo +3
Recently, safe reinforcement learning (RL) with the actor-critic structure for continuous control tasks has received increasing attention. It is still challenging to learn a near-o…
Robust Tube-based Model Predictive Control with Koopman Operators--Extended Version
Xinglong Zhang, Wei Pan, Riccardo Scattolini +2
Koopman operators are of infinite dimension and capture the characteristics of nonlinear dynamics in a lifted global linear manner. The finite data-driven approximation of Koopman…
CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels
Yongqian Xiao, Xin Xu, QianLi Lin
With the development of end-to-end control based on deep learning, it is important to study new system modeling techniques to realize dynamics modeling with high-dimensional inputs…
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles
Yongqian Xiao, Xinglong Zhang, Xin Xu +2
Autonomous driving technologies have received notable attention in the past decades. In autonomous driving systems, identifying a precise dynamical model for motion control is nont…
Robust Learning-based Predictive Control for Discrete-time Nonlinear Systems with Unknown Dynamics and State Constraints
Xinglong Zhang, Jiahang Liu, Xin Xu +2
Robust model predictive control (MPC) is a well-known control technique for model-based control with constraints and uncertainties. In classic robust tube-based MPC approaches, an…
A hierarchical Lyapunov-based cascade adaptive control scheme for lower-limb exoskeleton
Xinglong Zhang, Wei Jiang, Zhizhong Li +1
This paper proposes a hierarchical Lyapunov-based adaptive cascade control scheme for a lower-limb exoskeleton with control saturation. The proposed approach is composed by two con…
A Dual-level Model Predictive Control Scheme for Multi-timescale Dynamical Systems--Extended Version
Xinglong Zhang, Wei Jiang, Shuyou Yu +2
So far, many control algorithms have been developed for singularly perturbed systems. However, in many industrial processes, enforcing closed-loop fast-slow dynamics for peculiarly…
A hierarchical multirate MPC scheme for interconnected systems -
Marcello Farina, Xinglong Zhang, Riccardo Scattolini
This paper presents a hierarchical control scheme for interconnected linear systems. At the higher layer of the control structure a robust centralized Model Predictive Control (MPC…
A hierarchical MPC scheme for interconnected systems
Marcello Farina, Xinglong Zhang, Riccardo Scattolini
This paper describes a hierarchical control scheme for interconnected systems. The higher layer of the control structure is designed with robust Model Predictive Control (MPC) base…