Tuning of multi-loop PI controllers based on gain and phase margin specifications

In this paper, a single-iteration strategy is proposed for the design of a multi-loop PI controller to achieve the desired gain and phase margins for two-input and two-output (TITO) processes. To handle loop interactions, a TITO system is converted into two equivalent single loops with uncertainties drawn from interactions. The maximum uncertainty is estimated for the initial controller design in one loop and single-input and single-output (SISO) controller design is applied. This controller is substituted to other equivalent loop for design, and finally, the first loop controller is refined on knowledge of other loop controller. For SISO controller tuning, a new method is presented to determine the achievable gain and phase margins as well as the relevant controller parameters. Examples are given for illustration and comparison.     

混沌权值变异的Huffman树图像加密算法

提出一种采用混沌权值变异的Huff man树的图像加密算法.此算法在熵编码过程中,以基本的Huffman树为标准,利用双耦合混沌序列1对DC系数进行树的结构未变异、路径值变异的加密;再利用双耦合混沌序列2对AC系数进行码字序号的加密.论文对算法进行了仿真,并对安全性、计算复杂度、压缩比性能进行了分析.实验结果表明,该算法基本上不影响压缩效率,且计算复杂度低、安全性高和实时性好,可用于网络上的图像服务.     

Nanotextured superhydrophobic micromesh

A superhydrophobic micromesh covered with nanoprotrusions has been introduced and its applicability to a waterproof mobile phone speaker has been evaluated. The nanotextured superhydrophobic micromesh showed excellent water repellency, self-cleaning and waterproofing performances. In a waterproof speaker test using the fabricated nanotextured micromesh, the micromesh did not lose its waterproof function at 2 m water depth and did not form a remnant water film after being removed from the water. The packaged speaker showed almost the same sound quality before and after dipping at a 2 m water depth. These results demonstrate that the superhydrophobic nanotextured micromesh could be directly applicable for various products that need to resist water penetration, yet allow the transmission of gases and sound/light waves.     

Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities

This paper addresses the problems of stability and synchronization for a class of Markovian jump neural networks with partly unknown transition probabilities. We first study the stability analysis problem for a single neural network and present a sufficient condition guaranteeing the mean square asymptotic stability. Then based on the Lyapunov functional method and the Kronecker product technique, the chaos synchronization problem of an array of coupled networks is considered. Both the stability and the synchronization conditions are delay-dependent, which are expressed in terms of linear matrix inequalities. The effectiveness of the developed methods is shown by simulation examples.     

A belief-rule-based inventory control method under nonstationary and uncertain demand

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager’s knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate DFE by training BRB using historical demand data for generating reliable ordering policy.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Performance-First Control for Discrete-Time LQG Problems

Performance-first control for discrete-time LQG is considered in this paper to minimize the probability that the performance index exceeds a preselected threshold via constructing a closed-loop feedback control law. This problem can be converted into a mean-variance control problem which can be solved by developing a nested form of the variance and using polynomial optimization as a solution scheme.     

基于PIC16F877A的变频恒压供水控制器设计

分析了高层建筑供水控制系统的技术要求,介绍了基于PIC16F877A单片机的变频恒压供水控制器的工作原理,提出了该装置的软硬件设计方法.相比目前的变频恒压控制系统,该装置的精简硬件设计有效地克服了系统可靠性差的问题;同时,基于PSO-PID智能算法的软件设计解决了系统动态响应慢和压力调节不稳定的缺点.该装置成本低、智能化程度高,生产实际中能够确保设备的使用寿命、能源的有效利用和供水质量.因此,具有很高的推广、应用价值.