Peng Li

Orcid: 0000-0002-8217-1326

Affiliations:
  • Imperial College London, Department of Electrical and Electronic Engineering, UK


According to our database1, Peng Li authored at least 13 papers between 2016 and 2023.

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

Timeline

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Bibliography

2023
Fixed-Time Convergent Distributed Observer Design of Linear Systems: A Kernel-Based Approach.
IEEE Trans. Autom. Control., August, 2023

2022
Exponential Modulation Integral Observer for Online Detection of the Fundamental and Harmonics in Grid-Connected Power Electronics Equipment.
IEEE Trans. Control. Syst. Technol., 2022

Parameter Estimation for a Sinusoidal Signal with a Time-Varying Amplitude.
Proceedings of the European Control Conference, 2022

2020
Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems.
IEEE Trans. Autom. Control., 2020

Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems.
Eur. J. Control, 2020

2019
Deadbeat Source Localization From Range-Only Measurements: A Robust Kernel-Based Approach.
IEEE Trans. Control. Syst. Technol., 2019

Finite-time estimation of multiple exponentially-damped sinusoidal signals: A kernel-based approach.
Autom., 2019

2018
Non-asymptotic numerical differentiation: a kernel-based approach.
Int. J. Control, 2018

Deadbeat Simultaneous Parameter-State Estimation for Linear Continuous-time Systems: a Kernel-based Approach.
Proceedings of the 16th European Control Conference, 2018

Fast-Convergent Fault Detection and Isolation in an Uncertain Scenario.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
A deadbeat observer for LTI systems by time/output-dependent state mapping.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016
Kernel-based deadbeat parametric estimation of bias-affected damped sinusoidal signals.
Proceedings of the 15th European Control Conference, 2016

Estimation of multi-sinusoidal signals: A deadbeat methodology.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016


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