In this paper, a novel reconfiguration technique is developed in the context of a fault-tolerant Networked Control System (NCS) in two train wagons. All sensors, controllers and actuators in both wagons are connected ...In this paper, a novel reconfiguration technique is developed in the context of a fault-tolerant Networked Control System (NCS) in two train wagons. All sensors, controllers and actuators in both wagons are connected on top of a single Gigabit Ethernet network. The network also carries wired and wireless entertainment loads. A Markov model is used to prove that this reconfiguration technique reduces the effect of a failure in the error detection and switching mechanisms on the reliability of the control function. All calculations are based on closed-form solutions and verified using the SHARPE software package.展开更多
In this paper, a new reliable hierarchical model is suggested for a two-wagon train Networked Control System. Each wagon has a Controller that carries the control load and an Entertainment server that handles the ente...In this paper, a new reliable hierarchical model is suggested for a two-wagon train Networked Control System. Each wagon has a Controller that carries the control load and an Entertainment server that handles the entertainment. A supervisory controller runs on top of the two controllers and the two entertainment servers. Contrary to a similar model in the literature, the Supervisory node replaces a Controller as soon as it fails (Active Supervisor). All system states are analyzed and simulated using OPNET. It is shown that, for all states, this architecture has zero control packets dropped and the end-to-end delay is below the maximum target delay. A comparison between this Active model and the other model in the literature is presented. It is found that the entertainment in this new architecture is kept available for the passengers in more of the system states when compared to the architecture previously presented in the literature.展开更多
A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural langu...A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine （SVM） theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.展开更多
为降低现有列车网络控制系统(train control and management system,TCMS)端到端时延、抖动不确定性对列车控制功能时间确定性的影响,提高列车控制功能迭代效率,基于下一代列车网络控制系统(next generation TCMS,NG-TCMS),提出通信与...为降低现有列车网络控制系统(train control and management system,TCMS)端到端时延、抖动不确定性对列车控制功能时间确定性的影响,提高列车控制功能迭代效率,基于下一代列车网络控制系统(next generation TCMS,NG-TCMS),提出通信与计算资源联合调度模型,将端到端确定性从网络层延伸至列车控制功能。首先,结合NG-TCMS中时间敏感网络提供的全局统一时间基准,将列车控制功能拆分为具有依赖关系的状态采集、逻辑计算、数据转发、命令执行任务,并通过有向无环图进行形式化。以最小化执行时间为调度目标,分别通过一阶逻辑约束转化为可满足性模理论(satisfiability modulo theories,SMT)问题进行最优求解,以及抽象为整数线性规划(integer linear programming,ILP)问题进行最优求解。同时,提出基于任务松弛度和抖动继承值的快速求解方法,将一次性求解所有任务的大规模调度转化为迭代求解单任务或双任务的小规模调度,以解决控制功能数量陡增导致调度问题复杂度激增,SMT方法和ILP方法难以快速求解的问题。最后,参考CR450动车组列车控制功能设计算例,以30 min为求解时间上限,分析SMT方法、ILP方法、快速求解方法在求解时间与所得调度方案资源利用率方面的性能差异。结果表明,快速求解方法能在20 min内完成1000个含零抖动和抖动约束的控制功能调度,高效调度系统资源,满足NG-TCMS快速迭代需求。研究结果可为基于NG-TCMS构建具有端到端时间确定性的列车网络控制功能及任务调度方法提供参考。展开更多
文摘In this paper, a novel reconfiguration technique is developed in the context of a fault-tolerant Networked Control System (NCS) in two train wagons. All sensors, controllers and actuators in both wagons are connected on top of a single Gigabit Ethernet network. The network also carries wired and wireless entertainment loads. A Markov model is used to prove that this reconfiguration technique reduces the effect of a failure in the error detection and switching mechanisms on the reliability of the control function. All calculations are based on closed-form solutions and verified using the SHARPE software package.
文摘In this paper, a new reliable hierarchical model is suggested for a two-wagon train Networked Control System. Each wagon has a Controller that carries the control load and an Entertainment server that handles the entertainment. A supervisory controller runs on top of the two controllers and the two entertainment servers. Contrary to a similar model in the literature, the Supervisory node replaces a Controller as soon as it fails (Active Supervisor). All system states are analyzed and simulated using OPNET. It is shown that, for all states, this architecture has zero control packets dropped and the end-to-end delay is below the maximum target delay. A comparison between this Active model and the other model in the literature is presented. It is found that the entertainment in this new architecture is kept available for the passengers in more of the system states when compared to the architecture previously presented in the literature.
基金This work was partially supported by the Royal Society of UK and the National Natural Science Foundation of PRC (No. 60175028).
文摘A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine （SVM） theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.
文摘为降低现有列车网络控制系统(train control and management system,TCMS)端到端时延、抖动不确定性对列车控制功能时间确定性的影响,提高列车控制功能迭代效率,基于下一代列车网络控制系统(next generation TCMS,NG-TCMS),提出通信与计算资源联合调度模型,将端到端确定性从网络层延伸至列车控制功能。首先,结合NG-TCMS中时间敏感网络提供的全局统一时间基准,将列车控制功能拆分为具有依赖关系的状态采集、逻辑计算、数据转发、命令执行任务,并通过有向无环图进行形式化。以最小化执行时间为调度目标,分别通过一阶逻辑约束转化为可满足性模理论(satisfiability modulo theories,SMT)问题进行最优求解,以及抽象为整数线性规划(integer linear programming,ILP)问题进行最优求解。同时,提出基于任务松弛度和抖动继承值的快速求解方法,将一次性求解所有任务的大规模调度转化为迭代求解单任务或双任务的小规模调度,以解决控制功能数量陡增导致调度问题复杂度激增,SMT方法和ILP方法难以快速求解的问题。最后,参考CR450动车组列车控制功能设计算例,以30 min为求解时间上限,分析SMT方法、ILP方法、快速求解方法在求解时间与所得调度方案资源利用率方面的性能差异。结果表明,快速求解方法能在20 min内完成1000个含零抖动和抖动约束的控制功能调度,高效调度系统资源,满足NG-TCMS快速迭代需求。研究结果可为基于NG-TCMS构建具有端到端时间确定性的列车网络控制功能及任务调度方法提供参考。
