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Your search keyword '"Yu, Yongguang"' showing total 23 results
Start Over Author "Yu, Yongguang" Publisher ieee
23 results on '"Yu, Yongguang"'

2. Distributed Continuous-Time Optimization of Second-Order Multiagent Systems With Nonconvex Input Constraints.

Author

Mo, Lipo, Yu, Yongguang, Zhao, Lin, and Cao, Xianbing

Subjects
*MULTIAGENT systems, *ALGORITHMS, *DIFFERENTIABLE functions, *CONVEX functions, *TIME-varying systems
Abstract

This article discusses the distributed continuous-time optimization problem (DCTOP) of second-order multiagent systems (SOMASs). It is assumed that the inputs are required to be in some nonconvex sets, the team objective function (TOF) is a combination of general differentiable convex functions, and each agent can only obtain the information of one local objective function. Based on the neighbors’ information, a new distributed continuous-time optimization algorithm (DCTOA) is first proposed for each agent, where its gradient gains are nonuniform. By introducing a scaling factor and a model transformation, the corresponding system is changed into a time-varying nonlinear system which does not contain constraint operator in form. Then, it is proven that all agents’ states could reach an agreement and the TOF could be minimized by constructing some new Lyapunov functions. Finally, the effectiveness of the algorithm is shown by simulation results. [ABSTRACT FROM AUTHOR]

Published
2021
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3. Noise-Based Control of Opinion Dynamics.

Author

Su, Wei, Chen, Xianzhong, Yu, Yongguang, and Chen, Ge

Subjects
SOCIAL systems, SOCIAL dynamics, SOCIAL control, SOCIAL values, NOISE measurement
Abstract

Designing feasible control strategies for opinion dynamics in complex social systems has never been an easy task. It requires a control protocol, which 1) is not enforced on all individuals in the society, and 2) does not exclusively rely on specific opinion values shared by the social system. Thanks to the recent studies on noise-induced consensus in opinion dynamics, the noise-based intervention strategy has emerged as the only one meeting both of the above requirements, yet its underlying general theory is still lacking. In this article, we perform rigorous theoretical analysis and simulations of a noise-based control strategy for opinion formation, in which only a fraction of individuals is affected by randomly generated noise. We develop a new approach to prove the existence of a feasible noise protocol when it is difficult to be explicitly constructed and prove that irrespective of the number of noise-driven individuals, including the case of only one single noise-affected individual, the system can be controlled to achieve quasi-consensus in finite time, and the critical noise strength can be obtained. Our results highlight the efficiency of noise-driven mechanisms for the control of complex social dynamics. [ABSTRACT FROM AUTHOR]

Published
2022
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5. Event-Triggered Consensus of General Linear Multiagent Systems With Data Sampling and Random Packet Losses.

Author

Wang, Fei, Wen, Guoguang, Peng, Zhaoxia, Huang, Tingwen, and Yu, Yongguang

Subjects
MULTIAGENT systems, LINEAR matrix inequalities, LINEAR systems, BINOMIAL distribution, STATISTICAL sampling, STOCHASTIC systems
Abstract

This paper investigates the event-triggered consensus of linear multiagent systems with periodic data sampling mechanisms, where random packet losses are taken into account. The random packet losses occur in communication links based on a certain probability, and it is subject to the Bernoulli distribution. A novel distributed control protocol is designed based on the combined measurement to achieve the mean square consensus. By using the Riccati inequalities and linear matrix inequalities, an event-triggered condition with fewer parameters is also designed to reduce the information updating number. The interaction among the control gain matrix, sampling interval, and packet losses probability is used to describe the consensus conditions. The maximum sampling interval is presented explicitly. It is shown that the advantages of the proposed event-triggered strategy with the data sampling mechanism can avoid the Zeno behavior of the systems and continuous monitoring of the states. The simulations are provided to verify the proposed control strategy. [ABSTRACT FROM AUTHOR]

Published
2021
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9. The application of fuzzy-neural network on control strategy of hybrid vehicles

Author

Li Chunsheng, Meng Xia, Yu Yongguang, and Chen Rongguang

Subjects
Engineering, Adaptive neuro fuzzy inference system, State of charge, Adaptive control, business.industry, Control theory, Control system, Fuel efficiency, Fuzzy control system, business, Fuzzy logic, Driving cycle, Automotive engineering
Abstract

In order to increase the fuel economy and decrease the emissions of hybrid vehicles, firstly a fuzzy logic control system is presented in this paper. In parallel hybrid vehicles, the whole required torque comes from internal combustion engine and motor engine respectively. Based on the desired torque for driving and state of charge, the fuzzy logic control system determines how the power splits between the dual sources, which is the key point for hybrid vehicles. Then, adaptive neural-fuzzy inference system (ANFIS) method is applied to optimize fuzzy logic control system based on the data of driving cycle. The main contribution of this paper is well application of fuzzy-neural network to improve original control system, which minimized the fuel consumption and emissions. The simulation results show very good performance of the proposed method.

Published
2008

10. LMI Conditions for Global Stability of Fractional-Order Neural Networks.

Author

Zhang, Shuo, Yu, Yongguang, and Yu, Junzhi

Subjects
*LINEAR matrix inequalities, *ARTIFICIAL neural networks
Abstract

Fractional-order neural networks play a vital role in modeling the information processing of neuronal interactions. It is still an open and necessary topic for fractional-order neural networks to investigate their global stability. This paper proposes some simplified linear matrix inequality (LMI) stability conditions for fractional-order linear and nonlinear systems. Then, the global stability analysis of fractional-order neural networks employs the results from the obtained LMI conditions. In the LMI form, the obtained results include the existence and uniqueness of equilibrium point and its global stability, which simplify and extend some previous work on the stability analysis of the fractional-order neural networks. Moreover, a generalized projective synchronization method between such neural systems is given, along with its corresponding LMI condition. Finally, two numerical examples are provided to illustrate the effectiveness of the established LMI conditions. [ABSTRACT FROM AUTHOR]

Published
2017
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