The Design of Behavior Management Institution Based on Special Symbols and Measure Optimizing-Taking the Design of the Institution of Controlling the Pollution Behavior of Enterprises as an Example

Taking the institution design of controlling the pollution behavior of enterprises as an example, the symbol system specialized for the design and analysis of behavior management institution is put forward, which predigests the institution design greatly and make the process of institution design much like the engineering design. The measure combination method for improving the parameters of the institution, the arithmetic for calculating the validity of the institution and the arithmetic for calculating the behavior probability of the irrational managed are also put forward, which make the design and analysis technology of behavior management institution more practical.     

Performance comparison of distributed state estimation algorithms for power systems

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori (MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.     

Advance selling in the presence of product diffusion effect

Product diffusion refers to the phenomenon that the later demand is dependent on the early sales. To investigate how a firm’s advance selling strategy is affected by the effect of product diffusion, we consider a monopolist seller who sells a fashionable product in a market that comprises of myopic and strategic consumers over two periods (i.e., the advance selling season and the regular selling season). For a linear product diffusion effect we find that, when the effect of product diffusion is positive, the seller may set an extremely high advance selling price to induce the strategic consumers to purchase in the regular selling season, which is counter-intuitive. Moreover, the optimal procurement quantity for the seller may increase in the negative effect of product diffusion and decrease in the amount of strategic consumers. When we extend our model to consider a concave quadratic product diffusion effect, however, the optimal procurement quantity is concave in the amount of strategic consumers. Numerical studies are further presented to discuss the managerial insights.     

Knowledge-based bridge detection from SAR images

Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges’ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes: river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers’ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.     

采用DPWM3调制策略抑制异步电机系统的低频振荡

电压源型PWM逆变器控制的异步电动机变频调速系统运行中出现的低频振荡现象,影响了系统运行的质量和可靠性。从逆变器与电机匹配更加完善的角度,本文采用不连续空间矢量控制策略DPWM3,使低频振荡得到有效地抑制。     

Dynamic Event-Triggered Control for Nonlinear Systems: A Small-Gain Approach

An event-triggered control(ETC) system transmits data packages and updates control inputs only when the predefined criterion is satisfied. In this way, network communication and computing resources are scheduled more reasonably in contrast to the traditional periodic sampling strategy.Small-gain approach proposed in recent literatures is a new modeling method to deal with nonlinear ETC systems. Different from traditional ETC models, stability criteria are proposed in the form of input to state stability(ISS) gain to design the triggering mechanisms. This paper introduces additional dynamic variables in this model and proposes a small-gain based dynamic event-triggered strategy.Sufficient conditions to guarantee the stability of the system are derived with the help of cyclic-smallgain theorem and Zeno behaviors are avoided to ensure the feasibility of this method in practical applications. Numerical simulations are given to demonstrate the effectiveness of our approach.     

Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity

The identification of nonlinear systems with multiple sampled rates is a difficult task. The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data. Firstly, the auxiliary model identification principle is used to estimate the unmeasurable variables, and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the p...     

创新生态战略与创新效率关系：基于创新生态网络视角

基于创新生态系统理论,通过引入创新生态环境和创新生态位,构建一个有调节的中介效应模型,并基于长三角制造业企业调研数据,采用Bootstrap方法进行检验,探究创新生态战略通过创新生态网络对企业创新效率的作用机理。研究结果表明：创新生态战略对企业创新效率具有正向影响;创新生态网络在创新生态战略与企业创新效率关系中发挥中介作用;并且创新生态环境和创新生态位调节该中介效应。研究结果从创新生态网络视角构建了创新生态战略向企业创新效率转化的中间机制,丰富了创新生态系统理论研究。     

基于Unity3D的水下机器人半实物仿真系统

基于Unity3D研制了一种由地面控制终端、机器人本体和三维仿真系统3部分组成的水下机器人半实物仿真系统,为水下机器人开发过程中的性能测试、控制算法分析和人员操作培训提供了仿真和测试平台。该系统采用同一地面控制终端作为三维仿真系统和机器人控制系统的统一指令输入源,以实现虚拟对象和机器人本体的同步工作,可对系统进行实时监测、调参。采用多目视觉技术对机器人位置采集,对传感器数据进行卡尔曼滤波处理。机器人运动仿真试验结果表明,机器人实际运动路径和仿真规划路径基本相同,该系统动态响应性和控制系统同步性较好。