In this paper, the feasibility and objectives coordination of real-time optimization (RTO) are systemically investigated under soft constraints. The reason for requiring soft constraints adjustment and objective relax...In this paper, the feasibility and objectives coordination of real-time optimization (RTO) are systemically investigated under soft constraints. The reason for requiring soft constraints adjustment and objective relaxation simultaneously is that the result is not satisfactory when the feasible region is apart from the desired working point or the optimization problem is infeasible. The mixed logic method is introduced to describe the priority of the constraints and objectives, thereby the soft constraints adjustment and objectives coordination are solved together in RTO. A case study on the Shell heavy oil fractionators benchmark problem illustrating the method is finally presented.展开更多
This study proposes a virtual judging system for the Fosbury Flop based on the Timed Colored Petri Net(TCPN)and a Priority Constraint Matrix(PCM),aiming to enhance the accuracy and real-time capabilities of event judg...This study proposes a virtual judging system for the Fosbury Flop based on the Timed Colored Petri Net(TCPN)and a Priority Constraint Matrix(PCM),aiming to enhance the accuracy and real-time capabilities of event judging.First,an in-depth analysis of the judging requirements for the Fosbury Flop was conducted,defining key judgment nodes such as takeoff,bar clearance,and landing.A Petri net model was used to model the timing and state of each node.The system employs a PCM to control the execution order of judgment nodes,ensuring logical consistency and automation in the judging process.In simulation testing,the system’s judgment results in various scenarios-such as normal jumps,time violations,bar contact infractions,and unstable landings-were consistent with manual judgments,demonstrating high adaptability,stability,accuracy,and reliability.The results indicate that the virtual judging system can automatically recognize athlete actions and make judgments,effectively reducing human errors and providing innovative technical support for referee training and event management.Future research could incorporate more auxiliary resources to further optimize the system’s response speed,as well as integrate machine learning algorithms to enhance the intelligence and applicability of the judging system.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60474051) the Key Technology and Development Program of Shanghai Science and Technology Department (No. 04DZ11008) partly by the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20020248028).
文摘In this paper, the feasibility and objectives coordination of real-time optimization (RTO) are systemically investigated under soft constraints. The reason for requiring soft constraints adjustment and objective relaxation simultaneously is that the result is not satisfactory when the feasible region is apart from the desired working point or the optimization problem is infeasible. The mixed logic method is introduced to describe the priority of the constraints and objectives, thereby the soft constraints adjustment and objectives coordination are solved together in RTO. A case study on the Shell heavy oil fractionators benchmark problem illustrating the method is finally presented.
基金supported by the Educational Science Planning of Guangdong Province project of China(Grant Number:2023GXJK354)the Higher Education Teaching Research and Reform of Guangdong Province project of China in 2024.
文摘This study proposes a virtual judging system for the Fosbury Flop based on the Timed Colored Petri Net(TCPN)and a Priority Constraint Matrix(PCM),aiming to enhance the accuracy and real-time capabilities of event judging.First,an in-depth analysis of the judging requirements for the Fosbury Flop was conducted,defining key judgment nodes such as takeoff,bar clearance,and landing.A Petri net model was used to model the timing and state of each node.The system employs a PCM to control the execution order of judgment nodes,ensuring logical consistency and automation in the judging process.In simulation testing,the system’s judgment results in various scenarios-such as normal jumps,time violations,bar contact infractions,and unstable landings-were consistent with manual judgments,demonstrating high adaptability,stability,accuracy,and reliability.The results indicate that the virtual judging system can automatically recognize athlete actions and make judgments,effectively reducing human errors and providing innovative technical support for referee training and event management.Future research could incorporate more auxiliary resources to further optimize the system’s response speed,as well as integrate machine learning algorithms to enhance the intelligence and applicability of the judging system.
