Search Results for author: Imad M. Jaimoukha

Found 5 papers, 2 papers with code

A Real-Time Robust Ecological-Adaptive Cruise Control Strategy for Battery Electric Vehicles

no code implementations2 Aug 2023 Sheng Yu, Xiao Pan, Anastasis Georgiou, Boli Chen, Imad M. Jaimoukha, Simos A. Evangelou

This work addresses the ecological-adaptive cruise control problem for connected electric vehicles by a computationally efficient robust control strategy.

Computational Efficiency Model Predictive Control

A Computationally Efficient Robust Model Predictive Control Framework for Ecological Adaptive Cruise Control Strategy of Electric Vehicles

no code implementations21 Nov 2022 Sheng Yu, Xiao Pan, Anastasis Georgiou, Boli Chen, Imad M. Jaimoukha, Simos A. Evangelou

The control objective of the RMPC is to optimise the electric energy efficiency of the ego vehicle with consideration of a bounded model mismatch disturbance subject to satisfaction of physical and safety constraints.

Model Predictive Control

Computationally Efficient Robust Model Predictive Control for Uncertain System Using Causal State-Feedback Parameterization

no code implementations17 Aug 2022 Anastasis Georgiou, Furqan Tahir, Imad M. Jaimoukha, Simos A. Evangelou

This paper investigates the problem of robust model predictive control (RMPC) of linear-time-invariant (LTI) discrete-time systems subject to structured uncertainty and bounded disturbances.

Model Predictive Control

Blending Data and Physics Against False Data Injection Attack: An Event-Triggered Moving Target Defence Approach

1 code implementation27 Apr 2022 Wangkun Xu, Martin Higgins, Jianhong Wang, Imad M. Jaimoukha, Fei Teng

However, the uncontrollable false positive rate of the data-driven detector and the extra cost of frequent MTD usage limit their wide applications.

Robust Moving Target Defence Against False Data Injection Attacks in Power Grids

1 code implementation11 Nov 2021 Wangkun Xu, Imad M. Jaimoukha, Fei Teng

Recently, moving target defence (MTD) has been proposed to thwart false data injection (FDI) attacks in power system state estimation by proactively triggering the distributed flexible AC transmission system (D-FACTS) devices.

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