Yuan Zhao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Yuan Zhao has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Shihua Fu
School of Mathematical Sciences, Liaocheng University, Liaocheng, China
3 shared publications - Cheng Fu
School of Automation, Qingdao University, Qingdao 266071, China
1 shared publication - Hak-Keung Lam
Department of Engineering, King’s College London, London, U.K.
1 shared publication - Jianjun Wang
Research Center of Semi‐tensor Product of Matrices: Theory and Applications, School of Mathematical Sciences Liaocheng University Liaocheng P.R. China
1 shared publication - Jianli Zhao
Liaocheng University
1 shared publication - Jianwei Xia
Liaocheng University
1 shared publication
Latest Publications
- 4 March 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Vol. 56 (6) , 3550-3560
Decision-Oriented Fixed-Time Control for Multi-USVs in Pursuit–Evasion Game Subject to Exogenous Disturbances
This article investigates the pursuit–evasion (PE) game under the pure pursuit (or evasion) strategy for multi-uncrewed surface vehicles (USVs), along with the decision-oriented fixed-time velocity regulation controller (FTVRC) design. A novel exponential-type function approximation (ETFA) method is utilized to construct a differentiable performance index (PI), which reflects the decision-making basis for the player. Based on the differentiable PI, the player autonomously decides to generate the expected pursuit and evasion velocity, which includes size and direction information. To enable the player to execute its decision result, the FTVRC with a simple structure and low computational burden is designed to track the generated expected velocity. To cope with the unknown exogenous disturbances, a fixed-time disturbance observer (FTDO) is proposed to estimate the exogenous disturbances in real-time. According to the Lyapunov theory, all errors can achieve fixed-time convergence and the settling time is upper bounded. Finally, the simulation results show that the control scheme proposed in this article can achieve the PE target, and the superiorities of the ETFA method and the fixed-time control (FTC) method are demonstrated in the comparative simulations.
- 4 March 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Vol. 56 (6) , 3550-3560
Decision-Oriented Fixed-Time Control for Multi-USVs in Pursuit–Evasion Game Subject to Exogenous Disturbances
This article investigates the pursuit–evasion (PE) game under the pure pursuit (or evasion) strategy for multi-uncrewed surface vehicles (USVs), along with the decision-oriented fixed-time velocity regulation controller (FTVRC) design. A novel exponential-type function approximation (ETFA) method is utilized to construct a differentiable performance index (PI), which reflects the decision-making basis for the player. Based on the differentiable PI, the player autonomously decides to generate the expected pursuit and evasion velocity, which includes size and direction information. To enable the player to execute its decision result, the FTVRC with a simple structure and low computational burden is designed to track the generated expected velocity. To cope with the unknown exogenous disturbances, a fixed-time disturbance observer (FTDO) is proposed to estimate the exogenous disturbances in real-time. According to the Lyapunov theory, all errors can achieve fixed-time convergence and the settling time is upper bounded. Finally, the simulation results show that the control scheme proposed in this article can achieve the PE target, and the superiorities of the ETFA method and the fixed-time control (FTC) method are demonstrated in the comparative simulations.
- 3 April 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks and Learning Systems
- Vol. 36 (3) , 5334-5347
Dimensionality Reduction Method for the Output Regulation of Boolean Control Networks
This article proposes a dimensionality reduction approach to study the output regulation problem (ORP) of Boolean control networks (BCNs), which has much lower computational complexity than previous results. First, an auxiliary system which is much smaller in scale than the augmented system in previous approach is constructed. By analyzing the set stabilization of the auxiliary system as well as the original BCN, a necessary and sufficient condition to detect the solvability of the ORP is presented. Second, a method to design the state feedback controls for the ORP is proposed. Finally, two biological examples are given to demonstrate the effectiveness and advantage of the obtained new results.
- 3 April 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks and Learning Systems
- Vol. 36 (3) , 5334-5347
Dimensionality Reduction Method for the Output Regulation of Boolean Control Networks
This article proposes a dimensionality reduction approach to study the output regulation problem (ORP) of Boolean control networks (BCNs), which has much lower computational complexity than previous results. First, an auxiliary system which is much smaller in scale than the augmented system in previous approach is constructed. By analyzing the set stabilization of the auxiliary system as well as the original BCN, a necessary and sufficient condition to detect the solvability of the ORP is presented. Second, a method to design the state feedback controls for the ORP is proposed. Finally, two biological examples are given to demonstrate the effectiveness and advantage of the obtained new results.
- Open Access
- 2 November 2022
- Published by MDPI AG in Mathematics
- Vol. 10 (21) , 4078
Robust Output Tracking of Boolean Control Networks over Finite Time
With an increase in tracking time, the operating cost of the controller will increase accordingly. Considering the biological applications of Boolean control networks (BCNs), it is necessary to study the control problem of BCNs over finite time. In this paper, we study the output tracking problem of a BCN with disturbance inputs in a given finite time. First, the logical form of BCNs is transformed into an algebraic form using the semi-tensor product (STP) method. Then, the robust output tracking problems of a reference output trajectory and the outputs of a reference system over finite time are transformed into the robust reachability problem of the BCNs. Based on the truth matrix technique, two necessary and sufficient conditions are provided for the trackability of the reference outputs over finite time. Moreover, two algorithms are proposed to design the controllers in the case of the traceable outputs. It should be pointed out that the truth matrix method we used here has some unique features, including its simple computation and concise expression. Finally, two illustrative examples are presented to demonstrate the results in this paper.
- 2 November 2022
- Published by MDPI AG in Mathematics
- Vol. 10 (21) , 4078
Open AccessRobust Output Tracking of Boolean Control Networks over Finite Time
With an increase in tracking time, the operating cost of the controller will increase accordingly. Considering the biological applications of Boolean control networks (BCNs), it is necessary to study the control problem of BCNs over finite time. In this paper, we study the output tracking problem of a BCN with disturbance inputs in a given finite time. First, the logical form of BCNs is transformed into an algebraic form using the semi-tensor product (STP) method. Then, the robust output tracking problems of a reference output trajectory and the outputs of a reference system over finite time are transformed into the robust reachability problem of the BCNs. Based on the truth matrix technique, two necessary and sufficient conditions are provided for the trackability of the reference outputs over finite time. Moreover, two algorithms are proposed to design the controllers in the case of the traceable outputs. It should be pointed out that the truth matrix method we used here has some unique features, including its simple computation and concise expression. Finally, two illustrative examples are presented to demonstrate the results in this paper.
- 24 August 2022
- Published by Springer Nature in Dynamic Games and Applications
- Vol. 14 (2) , 508-523
Robust Strategy Optimization of Networked Evolutionary Games with Disturbance Inputs
- 24 August 2022
- Published by Springer Nature in Dynamic Games and Applications
- Vol. 14 (2) , 508-523
Robust Strategy Optimization of Networked Evolutionary Games with Disturbance Inputs