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
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.
