This paper presents an optimized shared control algorithm for human–AI interaction, implemented through a digital twin framework where the physical system and human operator act as the real agent while an AI-driven d...This paper presents an optimized shared control algorithm for human–AI interaction, implemented through a digital twin framework where the physical system and human operator act as the real agent while an AI-driven digital system functions as the virtual agent. In this digital twin architecture, the real agent acquires an optimal control strategy through observed actions, while the AI virtual agent mirrors the real agent to establish a digital replica system and corresponding control policy. Both the real and virtual optimal controllers are approximated using reinforcement learning(RL) techniques. Specifically, critic neural networks(NNs) are employed to learn the virtual and real optimal value functions, while actor NNs are trained to derive their respective optimal controllers. A novel shared mechanism is introduced to integrate both virtual and real value functions into a unified learning framework, yielding an optimal shared controller. This controller adaptively adjusts the confidence ratio between virtual and real agents, enhancing the system's efficiency and flexibility in handling complex control tasks. The stability of the closed-loop system is rigorously analyzed using the Lyapunov method. The effectiveness of the proposed AI–human interactive system is validated through two numerical examples: a representative nonlinear system and an unmanned aerial vehicle(UAV) control system.展开更多
The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers b...The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.展开更多
In this paper the linear multi-secret sharing schemes are studied by using monotone span programs. A relation between computing monotone Boolean functions by using monotone span programs and realizing multi-access str...In this paper the linear multi-secret sharing schemes are studied by using monotone span programs. A relation between computing monotone Boolean functions by using monotone span programs and realizing multi-access structures by using linear multi-secret sharing schemes is shown. Furthermore, the concept of optimal linear multi-secret sharing scheme is presented and the several schemes are proved to be optimal.展开更多
Multi terminal VSC-HVDC systems are a promising solution to the problem of connecting offshore wind farms to AC grids.Optimal power sharing and appropriate control of DC-link voltages are essential and must be maintai...Multi terminal VSC-HVDC systems are a promising solution to the problem of connecting offshore wind farms to AC grids.Optimal power sharing and appropriate control of DC-link voltages are essential and must be maintained dur-ing the operation of VSC-MTDC systems,particularly in post-contingency conditions.The traditional droop control methods cannot satisfy these requirements,and accordingly,this paper proposes a novel centralized control strategy based on a look-up table to ensure optimal power sharing and minimum DC voltage deviation immediately during post-contingency conditions by considering converter limits.It also reduces destructive effects(e.g.,frequency devia-tion)on onshore AC grids and guarantees the stable operation of the entire MTDC system.The proposed look-up table is an array of data that relates operating conditions to optimal droop coefficients and is determined according to N-1 contingency analysis and a linearized system model.Stability constraints and contingencies such as wind power changes,converter outage,and DC line disconnection are considered in its formation procedure.Simulations performed on a 4-terminal VSC-MTDC system in the MATLAB-Simulink environment validate the effectiveness and superiority of the proposed control strategy.展开更多
The dynamic frequency control processes and economic operations of the large-scale power grids are separately applied.However,for the small inertia microgrids(MGs),the operating conditions tend to be more volatile due...The dynamic frequency control processes and economic operations of the large-scale power grids are separately applied.However,for the small inertia microgrids(MGs),the operating conditions tend to be more volatile due to relatively more uncontrollable entities being integrated.Hence,the frequency control solution of MGs should take the economic operation of MGs at a time-scale that is much shorter than the traditional economic dispatch of the large power grids.To this end,this paper proposes a two-layer coordinated frequency control strategy for MGs with enhanced economic operation consideration.For the upper optimal power-sharing layer,the distributed bisection algorithm is applied to obtain the optimal power sharing among heterogeneous resources.For the lower control layer,an autonomous control strategy that integrates both primary control and secondary control reference is applied by adopting the event-trigger mechanism.The proposed control approach can realize integrated active power control of MGs by simultaneously taking primary control,secondary control,and economic operation into consideration.Simulation studies with a heterogeneous resources-powered MG demonstrate its effectiveness.展开更多
基金supported by China Postdoctoral Science Foundation(Project ID:2024M762602)the National Natural Science Foundation of China under Grant No.62306232Natural Science Basic Research Program of Shaanxi Province under Grant No.2023-JC-QN-0662.
文摘This paper presents an optimized shared control algorithm for human–AI interaction, implemented through a digital twin framework where the physical system and human operator act as the real agent while an AI-driven digital system functions as the virtual agent. In this digital twin architecture, the real agent acquires an optimal control strategy through observed actions, while the AI virtual agent mirrors the real agent to establish a digital replica system and corresponding control policy. Both the real and virtual optimal controllers are approximated using reinforcement learning(RL) techniques. Specifically, critic neural networks(NNs) are employed to learn the virtual and real optimal value functions, while actor NNs are trained to derive their respective optimal controllers. A novel shared mechanism is introduced to integrate both virtual and real value functions into a unified learning framework, yielding an optimal shared controller. This controller adaptively adjusts the confidence ratio between virtual and real agents, enhancing the system's efficiency and flexibility in handling complex control tasks. The stability of the closed-loop system is rigorously analyzed using the Lyapunov method. The effectiveness of the proposed AI–human interactive system is validated through two numerical examples: a representative nonlinear system and an unmanned aerial vehicle(UAV) control system.
基金Projects(71301115,71271150,71101102)supported by the National Natural Science Foundation of ChinaProject(20130032120009)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.
基金supported by the National Natural Science Foundation of China(Grant Nos.60083002,90304012,2004CB318000).
文摘In this paper the linear multi-secret sharing schemes are studied by using monotone span programs. A relation between computing monotone Boolean functions by using monotone span programs and realizing multi-access structures by using linear multi-secret sharing schemes is shown. Furthermore, the concept of optimal linear multi-secret sharing scheme is presented and the several schemes are proved to be optimal.
文摘Multi terminal VSC-HVDC systems are a promising solution to the problem of connecting offshore wind farms to AC grids.Optimal power sharing and appropriate control of DC-link voltages are essential and must be maintained dur-ing the operation of VSC-MTDC systems,particularly in post-contingency conditions.The traditional droop control methods cannot satisfy these requirements,and accordingly,this paper proposes a novel centralized control strategy based on a look-up table to ensure optimal power sharing and minimum DC voltage deviation immediately during post-contingency conditions by considering converter limits.It also reduces destructive effects(e.g.,frequency devia-tion)on onshore AC grids and guarantees the stable operation of the entire MTDC system.The proposed look-up table is an array of data that relates operating conditions to optimal droop coefficients and is determined according to N-1 contingency analysis and a linearized system model.Stability constraints and contingencies such as wind power changes,converter outage,and DC line disconnection are considered in its formation procedure.Simulations performed on a 4-terminal VSC-MTDC system in the MATLAB-Simulink environment validate the effectiveness and superiority of the proposed control strategy.
文摘The dynamic frequency control processes and economic operations of the large-scale power grids are separately applied.However,for the small inertia microgrids(MGs),the operating conditions tend to be more volatile due to relatively more uncontrollable entities being integrated.Hence,the frequency control solution of MGs should take the economic operation of MGs at a time-scale that is much shorter than the traditional economic dispatch of the large power grids.To this end,this paper proposes a two-layer coordinated frequency control strategy for MGs with enhanced economic operation consideration.For the upper optimal power-sharing layer,the distributed bisection algorithm is applied to obtain the optimal power sharing among heterogeneous resources.For the lower control layer,an autonomous control strategy that integrates both primary control and secondary control reference is applied by adopting the event-trigger mechanism.The proposed control approach can realize integrated active power control of MGs by simultaneously taking primary control,secondary control,and economic operation into consideration.Simulation studies with a heterogeneous resources-powered MG demonstrate its effectiveness.
