Yao Zhang

Orcid: 0000-0002-3821-371X

Affiliations:
  • Queen Mary University of London, UK


According to our database1, Yao Zhang authored at least 13 papers between 2014 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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Bibliography

2025
Robust sensing matrix design for the Orthogonal Matching Pursuit algorithm in compressive sensing.
Signal Process., 2025

2023
Robust model predictive control for constrained linear system based on a sliding mode disturbance observer.
Autom., August, 2023

2022
Modeling and Sliding-Mode Control for Launch and Recovery System in Predictable Sea States With Feasibility Check for Collision Avoidance.
IEEE Trans. Control. Syst. Technol., 2022

Prescribed Performance-Based Powered Descent Guidance for Step-Shaped Hazardous Terrains.
IEEE Trans. Aerosp. Electron. Syst., 2022

2020
Robust Excitation Force Estimation and Prediction for Wave Energy Converter M4 Based on Adaptive Sliding-Mode Observer.
IEEE Trans. Ind. Informatics, 2020

Fixed-Time Sliding Mode Control and High-Gain Nonlinearity Compensation for Dual-Motor Driving System.
IEEE Trans. Ind. Informatics, 2020

2019
Mars Powered Descent Phase Guidance Design Based on Fixed-Time Stabilization Technique.
IEEE Trans. Aerosp. Electron. Syst., 2019

Fixed-time sliding mode control based plant/controller co-design of dual-motor driving system.
Int. J. Syst. Sci., 2019

Wave Excitation Force Estimation for Wave Energy Converters Using Adaptive Sliding Mode Observer.
Proceedings of the 2019 American Control Conference, 2019

2018
Adaptive Finite-Time Disturbance Observer Based Sliding Mode Control for Dual-Motor Driving System.
Complex., 2018

2015
An improved reaching law of SMC for spacecraft tracking system.
Proceedings of the IEEE International Conference on Information and Automation, 2015

2014
An Aeromagnetic Compensation Algorithm for Aircraft Based on Fuzzy Adaptive Kalman Filter.
J. Appl. Math., 2014

Control Input Saturation Sliding-Mode Control System Design for Spacecraft Based on Neural Network.
Proceedings of the Seventh International Joint Conference on Computational Sciences and Optimization, 2014


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