Outputs (8)

Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems (2021)
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 investigated systems. In particular, the system model is formulated by a st... Read More about Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems.

An efficient message passing algorithm for decentrally controlling complex systems (2021)
Journal Article
Herzallah, R., & Zhou, Y. (2023). An efficient message passing algorithm for decentrally controlling complex systems. International Journal of Control, 96(3), 719-730. 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 probabilistic control and message passing architecture of mutually interacting... Read More about An efficient message passing algorithm for decentrally controlling complex systems.

Probabilistic message passing control for complex stochastic switching systems (2021)
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 models are exploited to characterise the subsystems’ dynamical behaviours cons... Read More about Probabilistic message passing control for complex stochastic switching systems.

Probabilistic decentralised control and message passing framework for future grid (2021)
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 development of the future smart grid. The key elements of the proposed framework are... Read More about Probabilistic decentralised control and message passing framework for future grid.

Probabilistic message passing control and FPD based decentralised control for stochastic complex systems (2020)
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 main challenges in controlling complex systems such as high dimensionality... Read More about Probabilistic message passing control and FPD based decentralised control for stochastic complex systems.

A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise (2020)
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 constraints of certain distributions. The general solution to the fully probabilist... Read More about A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise.

Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter (2019)
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 and non-Gaussian stochastic dynamic processes with unmeasurable states. The s... Read More about Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter.

EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems (2017)
Journal Article
Zhou, Y., Zhang, Q., Wang, H., Zhou, P., & Chai, T. (2018). EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems. IEEE Transactions on Automatic Control, 63(4), 1155-1162. https://doi.org/10.1109/tac.2017.2742661

In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be us... Read More about EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems.