The content based image retrieval (CBIR) is aimed to find the most similar images from a collection of images or a database to the query image according to the visual or semantic similarity. Current image retrieval al...
详细信息
As the complex anatomical structure of the maxillofacial region, operation in this area is of high hazard and difficult to implement. Thus, a multi-arm medical robot assisting maxillofacial surgery, which can improve ...
详细信息
Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targe...
详细信息
Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targets with complex properties. In this paper, a method for 3D deployment optimization of sensor network based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. Many factors such as coverage scale, detection probability and resource utilization are synthetically considered to optimize the sensor network's overall detection performance. To evaluate the network's performance, four indexes are presented and the 3D deployment space is divided into different height levels. Accordingly, the mathematical model is formulated by weighting the performance indexes and height levels due to their importance degrees. In order to solve the optimization problem, an algorithm called WCPSO is carried out, which has a dynamic inertia weight and adaptable acceleration constants. Verified by the simulation results, the presented 3D deployment optimization method effectively improves the sensor network's detection performance. The method in this paper can provide guidance and technical reference in future application of relevant research.
A small humanoid robot with a teleoperation system using 3G communication network is present in this paper. Considering the requirement of dynamic environment and hardware limitations of small humanoid, the teleoperat...
详细信息
ISBN:
(纸本)9781467321259
A small humanoid robot with a teleoperation system using 3G communication network is present in this paper. Considering the requirement of dynamic environment and hardware limitations of small humanoid, the teleoperation system was designed using 3G communication network, which has a good performance both on the long-distance operation and the communication speed. Then an improved walking planning method is explored on this robot. Most of conventional walking planning methods can not fit to the low computation performance of small humanoid nor the real-time teleoperation requirement. In order to solve this problem, an online walking planning method with has been presented in this paper. There are two primary advantages compared with conventional walking planning methods. First, the new online walking planning can realize walking based on real-time tasks due to its short control period. Secondly, the reduced computation and walking data can fit to the hardware limit of the small humanoid. The effectiveness of the proposed walking planning method was confirmed by experiments.
This article considers the problem of optimal guidance laws for cooperative attack of multiple missiles based on the optimal control theory. New guidance laws are presented such that multiple missiles attack a single ...
详细信息
This article considers the problem of optimal guidance laws for cooperative attack of multiple missiles based on the optimal control theory. New guidance laws are presented such that multiple missiles attack a single target simultaneously. Simulation results show the effectiveness of the proposed algorithms. [PUBLICATION ABSTRACT]
This paper is devoted to the fault detection of linear systems over networks with bounded packet loss . The inputs and the measurements of the monitored system are transmitted to a fault detection node over an unrelia...
This paper is devoted to the fault detection of linear systems over networks with bounded packet loss . The inputs and the measurements of the monitored system are transmitted to a fault detection node over an unreliable network with bounded packet loss. The packet loss process is assumed to be arbitrary or Markovian in this paper. Due to the bounded packet loss process, the monitored system is modeled as a switched system by re-sampling it at each time instant when the measurements arrive at the fault detection node. A fault detection filter for this switched system is designed in this paper to satisfy some performance constraints. The filter updates only at the time instant when new measurements arrive at the fault detection node and the input data packets' lost are considered as external disturbances . Finally, the numerical example and simulations have demonstrated the usefulness of the proposed method.
This article considers a centralised data fusion system, in which the measurements of the local sensors are time-stamped, and then transmitted through the network to the fusion centre. The system will suffer measureme...
详细信息
This article considers a centralised data fusion system, in which the measurements of the local sensors are time-stamped, and then transmitted through the network to the fusion centre. The system will suffer measurements delay or loss due to the unreliability of the network. Based on the Kalman filter and information filter in a single channel, a centralised data fusion algorithm with buffers is proposed to solve this problem. A probabilistic metric to evaluate the performance of the system is presented. Simulation results show the effectiveness of the proposed method.
作者:
Zhongjing MaSchool of Automation
Beijing Institute of Technology (BIT) and the Key Laboratory of Complex System Intelligent Control and Decision (BIT) Ministry of Education
Optimal charging control of large-population autonomous plug-in electric vehicles (PEVs) in power grid can be formulated as a class of constrained non-linear timevariant optimization problems. To overcome the computat...
详细信息
Optimal charging control of large-population autonomous plug-in electric vehicles (PEVs) in power grid can be formulated as a class of constrained non-linear timevariant optimization problems. To overcome the computational complexity of this class of optimization problems, the author and his collaborators proposed a game-based decentralized control method such that individual agents update their best charging strategies simultaneously with respect to a common electricity price signal which is determined by the total demand in the grid. Due to the heterogeneity of individual PEVs, the game systems converge to a nearly valley-fill NE strategy with nontrivial deviation costs due to the heterogeneity property of individual PEV charging characteristics. In this paper the author proposed a novel algorithm to implement the optimal decentralized valley fill strategies for the charging problems of the PEV population which is composed of disjoint homogeneous subpopulations. The author introduces a cost which penalizes against the deviation of strategy of individual agent in a subpopulation from the average value of the subpopulation. It can be shown that in case that the update algorithm converges, the system reaches the optimal valley-fill equilibrium strategy where the introduced agent deviation cost vanishes. Simulation examples are used to illustrate the results developed in this paper.
—In this paper, a synchronization of discrete multi-agent systems with random network delays was studied. By employing the graph and matrix theory, a model based predictive control algorithm is proposed to achieve le...
详细信息
—In this paper, a synchronization of discrete multi-agent systems with random network delays was studied. By employing the graph and matrix theory, a model based predictive control algorithm is proposed to achieve leader-following consensus in a network of agents. Furthermore, a consensus protocol is developed based on this strategy. Numerical simulation examples are provided to illustrate the effectiveness of the theoretical results.
In this paper, the Bouc-Wen model widely used in describing hysteretic systems is applied to piezoelectric actuator (PEA) modelling and real-coded adaptive genetic algorithm (GA) is adopted to identify the model param...
详细信息
ISBN:
(纸本)9787900769428
In this paper, the Bouc-Wen model widely used in describing hysteretic systems is applied to piezoelectric actuator (PEA) modelling and real-coded adaptive genetic algorithm (GA) is adopted to identify the model parameters simultaneously. By dynamically adjusting the crossover probability and mutation probability, adaptive genetic algorithm improves the performance of local convergence and premature convergence and enhances search speed and precision of the simple genetic algorithm. Then some experiments are conducted to verify the efficiency of the identification method with satisfactory parameter identification results.
暂无评论