In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and...In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and applying them to separate identification of nonlinear multi-variable systems is introduced and discussed.展开更多
As wireless sensor network becomes pervasive, new requirements have been continuously emerged. How-ever, the most of research efforts in wireless sensor network are focused on energy problem since the nodes are usuall...As wireless sensor network becomes pervasive, new requirements have been continuously emerged. How-ever, the most of research efforts in wireless sensor network are focused on energy problem since the nodes are usually battery-powered. Among these requirements, real-time communication is one of the big research challenges in wireless sensor networks because most of query messages carry time information. To meet this requirement, recently several real-time medium access control protocols have been proposed for wireless sensor networks in the literature because waiting time to share medium on each node is one of main source for end-to-end delay. In this paper, we first introduce the specific requirement of wireless sensor real-time MAC protocol. Then, a collection of recent wireless sensor real-time MAC protocols are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally we present a dis-cussion about the challenges of current wireless sensor real-time MAC protocols in the literature, and show the conclusion in the end.展开更多
A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and i...A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.展开更多
Intellectualization of sheet metal in deep drawing is a new combined technology, which is concerned with control science and computer science and sheet metal forming theory. The intelligent control system for sheet me...Intellectualization of sheet metal in deep drawing is a new combined technology, which is concerned with control science and computer science and sheet metal forming theory. The intelligent control system for sheet metal deep drawing consists of four fundamental factors: real time measurement, identification, prediction and control. Real time identification of material properties and friction coefficient is the most important factor in the whole system. An artificial neural network model for identification of the material properties and friction coefficient was established according to deep drawing characteristics and more automation. The identification of the material properties and friction coefficient was realized.展开更多
A complete scheme for solving the key scientific problems associated with high-standard,high-intensity continuous construction of high arch dams was presented. First,based on a coupling analysis of construction system...A complete scheme for solving the key scientific problems associated with high-standard,high-intensity continuous construction of high arch dams was presented. First,based on a coupling analysis of construction system decomposition and coordination for a high arc dam,a mathematical model for real-time control of construction quality and progress that considers complex constraints was developed. Second,a method of progress control was proposed based on a dynamic simulation. Third,a dynamic quality control mechanism was established based on construction information collected using a PDA. Fourth,a system for integrating collected information,progress simulation and quality control analyses under a network environment was developed. Finally,these methods were applied to a practical project to show that each aspect of a construction process can be managed effectively and that real-time monitoring and feedback control can be realized. Our methods provide new theoretical principles and technical measures for quality and progress control in the high arc dam construction process.展开更多
基金Supported by National Naturai Science Foundation of China （61273104, 61021002, 61104097）, and Projects of Major Interna-tional （Regional） Joint Research Program National Natural Science Foundation of China （61120106010）
文摘In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and applying them to separate identification of nonlinear multi-variable systems is introduced and discussed.
文摘As wireless sensor network becomes pervasive, new requirements have been continuously emerged. How-ever, the most of research efforts in wireless sensor network are focused on energy problem since the nodes are usually battery-powered. Among these requirements, real-time communication is one of the big research challenges in wireless sensor networks because most of query messages carry time information. To meet this requirement, recently several real-time medium access control protocols have been proposed for wireless sensor networks in the literature because waiting time to share medium on each node is one of main source for end-to-end delay. In this paper, we first introduce the specific requirement of wireless sensor real-time MAC protocol. Then, a collection of recent wireless sensor real-time MAC protocols are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally we present a dis-cussion about the challenges of current wireless sensor real-time MAC protocols in the literature, and show the conclusion in the end.
文摘A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.
文摘Intellectualization of sheet metal in deep drawing is a new combined technology, which is concerned with control science and computer science and sheet metal forming theory. The intelligent control system for sheet metal deep drawing consists of four fundamental factors: real time measurement, identification, prediction and control. Real time identification of material properties and friction coefficient is the most important factor in the whole system. An artificial neural network model for identification of the material properties and friction coefficient was established according to deep drawing characteristics and more automation. The identification of the material properties and friction coefficient was realized.
基金supported by the National Basic Research Program of China("973"Project)(Grant No.2007CB714101)the National Key Technology R&D Program in the11th Five-year Plan of China(Grant No.2008BAB29B0501)the National Natural Science Foundation of China(Grant No.90815019)
文摘A complete scheme for solving the key scientific problems associated with high-standard,high-intensity continuous construction of high arch dams was presented. First,based on a coupling analysis of construction system decomposition and coordination for a high arc dam,a mathematical model for real-time control of construction quality and progress that considers complex constraints was developed. Second,a method of progress control was proposed based on a dynamic simulation. Third,a dynamic quality control mechanism was established based on construction information collected using a PDA. Fourth,a system for integrating collected information,progress simulation and quality control analyses under a network environment was developed. Finally,these methods were applied to a practical project to show that each aspect of a construction process can be managed effectively and that real-time monitoring and feedback control can be realized. Our methods provide new theoretical principles and technical measures for quality and progress control in the high arc dam construction process.
