most citedData-driven sliding mode control for partially unknown nonlinear systems

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control

Maxiu Xiao, Jianglin Lan, Jingxin Yu +3

Climate control is crucial for greenhouse production as it directly affects crop growth and resource use. Reinforcement learning (RL) has received increasing attention in this fiel…

eess.SY2024

An integrated design of robust decentralized observer and controller for load frequency control

Xianxian Zhao, Jianglin Lan

This paper focuses on designing completely decentralized load frequency control (LFC) for multi-area power systems to achieve global optimized performance. To this end, a new conce…

eess.SY2024

Safe Stabilization using Nonsmooth Control Lyapunov Barrier Function

Jianglin Lan, Eldert van Henten, Peter Groot Koerkamp +1

This paper addresses the challenge of safe stabilization, ensuring the system state reach the origin while avoiding unsafe regions. Existing approaches relying on smooth Lyapunov b…

eess.SY2024

Runtime Monitoring and Fault Detection for Neural Network-Controlled Systems

Jianglin Lan, Siyuan Zhan, Ron Patton +1

There is an emerging trend in applying deep learning methods to control complex nonlinear systems. This paper considers enhancing the runtime safety of nonlinear systems controlled…

eess.SY2024★ 2 cited

Data-driven sliding mode control for partially unknown nonlinear systems

Jianglin Lan, Xianxian Zhao, Congcong Sun

This paper presents a new data-driven control for multi-input, multi-output nonlinear systems with partially unknown dynamics and bounded disturbances. Since exact nonlinearity can…