Edinburgh Napier University

Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions

Journal Article

Liu, J., Zhang, Y., Zhou, Y., & Chen, J. (2024)

Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions. Mathematics, 12(5), Article 667. https://doi.org/10.3390/math12050667

This study presents a novel event-triggered relearning framework for neural network modeling, designed to improve prediction precision in dynamic stochastic complex industrial...

Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems

Journal Article

Tang, X., Zhou, Y., Zou, Y., & Zhang, Q. (2022)

Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems. Entropy, 24(1), Article 25. https://doi.org/10.3390/e24010025

This paper investigates the randomness assignment problem for a class of continuous-time stochastic nonlinear systems, where variance and entropy are employed to describe the ...

An efficient message passing algorithm for decentrally controlling complex systems

Journal Article

Herzallah, R., & Zhou, Y. (in press)

An efficient message passing algorithm for decentrally controlling complex systems. International Journal of Control, https://doi.org/10.1080/00207179.2021.2011422

This paper proposes a decentralised stochastic control framework for a class of large-scale and complex dynamic networks. The proposed framework describes a decentralised prob...

Probabilistic message passing control for complex stochastic switching systems

Journal Article

Zhou, Y., & Herzallah, R. (2021)

Probabilistic message passing control for complex stochastic switching systems. Journal of The Franklin Institute, 358(10), 5451-5469. https://doi.org/10.1016/j.jfranklin.2021.04.040

In this paper, we propose a general decentralised probabilistic control framework for a class of complex stochastic systems with switching modes. Probabilistic state space mod...

Probabilistic decentralised control and message passing framework for future grid

Journal Article

Herzallah, R., & Zhou, Y. (2021)

Probabilistic decentralised control and message passing framework for future grid. International Journal of Electrical Power and Energy Systems, 131, Article 107114. https://doi.org/10.1016/j.ijepes.2021.107114

In this paper, we propose a unified probabilistic decentralised control and message passing framework for real time control of the electrical grid which enables the developmen...

Optimal Electricity Trading Strategy for a Household Microgrid

Conference Proceeding

Qin, Z., Hua, H., Liang, H., Herzallah, R., Zhou, Y., & Cao, J. (2020)

Optimal Electricity Trading Strategy for a Household Microgrid. In 2020 IEEE 16th International Conference on Control & Automation (ICCA). https://doi.org/10.1109/icca51439.2020.9264421

The recent integration of distributed generators (DGs) and renewable energy sources (RESs) into the power system led to the manifestation of a significant number of household ...

Probabilistic message passing control and FPD based decentralised control for stochastic complex systems

Journal Article

Zhou, Y., & Herzallah, R. (2020)

Probabilistic message passing control and FPD based decentralised control for stochastic complex systems. AIMS Electronics and Electrical Engineering, 4(2), 216-233. https://doi.org/10.3934/electreng.2020.2.216

This paper offers a novel decentralised control strategy for a class of linear stochastic largescale complex systems. The proposed control strategy is developed to address the...

A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise

Journal Article

Herzallah, R., & Zhou, Y. (2020)

A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise. Journal of Vibration and Control, 26(23-24), 2329-2339. https://doi.org/10.1177/1077546320921608

This article proposes the exploitation of the Kullback–Leibler divergence to characterise the uncertainty of the tracking error for general stochastic systems without constrai...

Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter

Journal Article

Zhou, Y., Wang, A., Zhou, P., Wang, H., & Chai, T. (2020)

Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter. Automatica, 112, Article 108693. https://doi.org/10.1016/j.automatica.2019.108693

In this paper, a novel hybrid control method is proposed to enhance the tracking performance of the Proportional–Integral (PI) based control system for a class of nonlinear an...

Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

Conference Proceeding

Zhou, Y., Herzallah, R., & Zafar, A. (2019)

Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise. In 2019 IEEE 15th International Conference on Control and Automation (ICCA). https://doi.org/10.1109/icca.2019.8899607

In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared w...