In this paper,the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method.Firstly,a centralized observer which makes use of the me...In this paper,the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method.Firstly,a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems.The mobile agents,each of which is affixed with a controller and an actuator,can provide the observer-based control for the target systems.By using Lyapunov stability arguments,the stability for the estimation error system and distributed parameter control system is proved,meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance.A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches.展开更多
Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direc...Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direction, this paper describes collaborative estimation and control algorithms design for WSANs. First, a sensor-actuator coordination model is proposed based on distributed Kalman filter in federated configuration. This method provides the capability of fault tolerance and multi-source information fusion. On this basis, an actuator-actuator coordination model based on even-driven task allocation is introduced. Actuators utilize fused sensory information to adjust their action that incur the minimum energy cost to the system subject to the constraints that user＇s preferences regarding the states of the system are approximately satisfied. Finally, according to system requirements, a distributed algorithm is proposed to solve the task allocation problem. Simulations demonstrate the effectiveness of our proposed methods.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61174021 and 61473136)the 111 Project of China(Grant No.B12018)
文摘In this paper,the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method.Firstly,a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems.The mobile agents,each of which is affixed with a controller and an actuator,can provide the observer-based control for the target systems.By using Lyapunov stability arguments,the stability for the estimation error system and distributed parameter control system is proved,meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance.A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches.
基金supported by the National Natural Science Foundation of China(No.61174070)the Specialized Research Fund for the Doctoral Program(No.20110172110033)
文摘Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direction, this paper describes collaborative estimation and control algorithms design for WSANs. First, a sensor-actuator coordination model is proposed based on distributed Kalman filter in federated configuration. This method provides the capability of fault tolerance and multi-source information fusion. On this basis, an actuator-actuator coordination model based on even-driven task allocation is introduced. Actuators utilize fused sensory information to adjust their action that incur the minimum energy cost to the system subject to the constraints that user＇s preferences regarding the states of the system are approximately satisfied. Finally, according to system requirements, a distributed algorithm is proposed to solve the task allocation problem. Simulations demonstrate the effectiveness of our proposed methods.
