Dear Editor,This letter proposes a robust distributed model predictive control(MPC) strategy for formation tracking of a group of wheeled vehicles subject to constraints and disturbances. Formation control has attract...Dear Editor,This letter proposes a robust distributed model predictive control(MPC) strategy for formation tracking of a group of wheeled vehicles subject to constraints and disturbances. Formation control has attracted significant interest because of its applications in searching and exploration [1], [2].展开更多
This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the...This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the target can be detected by any robot and captured successfully by two or more robots.In this paper,we assume that each robot has a limited communication range.We maintain the robots within a mobile network to guarantee the successful capture.In addition,the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time.A coordination algorithm considering both aspects is proposed.This algorithm can greatly reduce the expected time of capturing the mobile target.Finally,we validate the algorithm by the simulations and experiments.展开更多
We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our t...We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our tradeoff model is the first one that incorporates time slots allocation into this framework. By using Lagrangian dual decomposition method, we decompose the tradeoff model into two subproblems： routing problem at network layer and resource allocation problem at medium access control （MAC） layer. The interfaces between the layers are precisely the dual variables. A partially distributed algorithm is proposed to solve the nonlinear, convex, and separable tradeoff model. Numerical simulation results are presented to support our algorithm.展开更多
基金supported by the National Natural Science Foundation of China (62073015, 62173016)。
文摘Dear Editor,This letter proposes a robust distributed model predictive control(MPC) strategy for formation tracking of a group of wheeled vehicles subject to constraints and disturbances. Formation control has attracted significant interest because of its applications in searching and exploration [1], [2].
基金supported by the National Natural Science Foundation of China(No.60434030)
文摘This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the target can be detected by any robot and captured successfully by two or more robots.In this paper,we assume that each robot has a limited communication range.We maintain the robots within a mobile network to guarantee the successful capture.In addition,the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time.A coordination algorithm considering both aspects is proposed.This algorithm can greatly reduce the expected time of capturing the mobile target.Finally,we validate the algorithm by the simulations and experiments.
基金supported by the Natural Science Foundation of China(No.60704046,60725312,60804067)the National 863 High Technology Research and Development Plan(No.2007AA04Z173,2007AA041201)
文摘We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our tradeoff model is the first one that incorporates time slots allocation into this framework. By using Lagrangian dual decomposition method, we decompose the tradeoff model into two subproblems： routing problem at network layer and resource allocation problem at medium access control （MAC） layer. The interfaces between the layers are precisely the dual variables. A partially distributed algorithm is proposed to solve the nonlinear, convex, and separable tradeoff model. Numerical simulation results are presented to support our algorithm.
