Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.     

Adaptive ILC algorithms of nonlinear continuous systems with non-parametric uncertainties for non-repetitive trajectory tracking

In this article, two adaptive iterative learning control (ILC) algorithms are presented for nonlinear continuous systems with non-parametric uncertainties. Unlike general ILC techniques, the proposed adaptive ILC algorithms allow that both the initial error at each iteration and the reference trajectory are iteration-varying in the ILC process, and can achieve non-repetitive trajectory tracking beyond a small initial time interval. Compared to the neural network or fuzzy system-based adaptive ILC schemes and the classical ILC methods, in which the number of iterative variables is generally larger than or equal to the number of control inputs, the first adaptive ILC algorithm proposed in this paper uses just two iterative variables, while the second even uses a single iterative variable provided that some bound information on system dynamics is known. As a result, the memory space in real-time ILC implementations is greatly reduced.     

Machining activity extraction and energy attributes inheritance method to support intelligent energy estimation of machining process

An energy-efficient intelligent manufacturing system could significantly save energy compared to traditional intelligent manufacturing systems that do not consider energy issues. Intelligent energy estimation of machining processes is the foundation of the energy-efficient intelligent manufacturing system. This paper proposes a method for machining activity extraction and energy attributes inheritance to support the intelligent energy estimation of machining processes. Fifteen machining activities and their energy attributes are defined according to their operating and energy consumption characteristics. Activities and energy attributes are extracted mainly from NC program supplemented with blank dimensional information. An effective extraction method of activities and energy attributes is the basis for the intelligent energy calculating of machining process. Based on an investigation on the extraction procedure of activities and energy attributes, energy attributes inheritance method is further discussed. Four types of energy attribute inheritance rules are summarized according to the different inheritance characteristics. Based on these four types of inheritance rules, the energy attributes can be transmitted from activity to Therblig as effective inputs of Therblig-based energy model of machining processes. The proposed methodology is finally demonstrated through two machining cases.     

Multimedia cloud transmission and storage system based on internet of things

For the issues of large space and storage security of multimedia files, we analyzed the impact of access control and cloud storage on multimedia file, and proposed a mixed security cloud storage framework based on Internet of Things. This paper introduced the concept of multimedia protection into the method based on role access control. Moreover, we also adopted a scheme based on the combination of multimedia data state and role access control. At the same time, all input and output devices were connected to this system. Internet of Things is used to judge whether circuits are connected and whether the devices are normally operated, so as to improve the access efficiency. On this basis, we also described in detail the complete process of registration, role assignment, multimedia file owner’s request for data encryption, and user login and access to multimedia file. According to the result, this scheme can be used to resist the known attacks. It guarantees security of multimedia files.     

Iterative quadtree decomposition based automatic selection of the seed point for ultrasound breast tumor images

Based on seed region growing method, lesion segmentation for ultrasound breast tumor images often requires manual selection of the seed point, which is both time-consuming and laborious. To overcome this limit, this paper attempts to explore an automatic method for finding the seed point inside the tumor. Two criteria combining iterative quadtree decomposition (QTD) and the gray characteristics of the lesion are thus designed to locate the seed point. One is to seek the biggest homogenous region and the other is to select the seed region where the seed point is found. Furthermore, this study validates the proposed algorithm through 110 ultrasonic breast tumor images (including 58 malignant tumor images and 52 benign tumor images). According to the needs of the seed region growing algorithm, if the seed point is found inside the tumor, it means the proposed method is correct. Otherwise, it means that the method is a failure. As the quantitative experiment results show, the proposed method in this paper can automatically find the seed point inside the tumor with an accuracy rate of 97.27 %.     

峰值电流模升压转换器的动态斜坡补偿电路设计

基于HHNEC 0.35 μm BCD工艺设计了一种应用于峰值电流模升压转换器的动态斜坡补偿电路.该电路能够跟随输入输出信号变化,相应给出适当的补偿量,从而避免了常规斜坡补偿所带来的系统带载能力低及瞬态响应慢等问题.经Cadence Spectre验证,该电路能够达到设计要求.     

数据融合技术在智能交通系统中的应用

为了更加准确地监测动态变化的交通信息,通过分析城市道路交通流量变化的特点,提出一种基于数据融合的监测方法。根据数据属性的特点,将数据构造为多个相关的时间序列,在此基础上进行数据融合,以最终的结果对交通信号灯进行实时控制,保证道路通畅。仿真实验结果证明,该方法具有较高的判断准确率和良好的识别性能。     

HEDP及其取代物对碳酸钙阻垢机理的研究

采用分子动力学方法,模拟计算了阻垢剂HEDP及其取代物与方解石(104,(102),(202),(113)面的相互作用,计算并分析了阻垢剂与方解石(104),(102),(202),(113)面作用的相互作用能,包括结合能,库仑能和范德华作用能.并且分析了方解石(104)晶面上的钙离子与阻垢剂中双键氧原子、整个(104)晶面与阻垢剂中所有氧原子之间和整个(104)晶面与整个阻垢剂分子之间的对关联函数,结果表明:阻垢剂分子中的氧原子与碳酸钙的Ca2+形成的离子键对吸附起到了主要作用,同时阻垢剂与晶面间存在较弱的范德华力相互作用,阻垢剂与各晶面的的结合能强弱顺序为(102)＞(202)≥(113)≈(104).苯环的大π键有利于阻垢效果的提高.     

基于ARM及GPRS技术的AMR系统设计

该文提出了一种基于ARM及GPRS技术的AMR(Automatic Meter Reading,自动抄表)系统设计的解决方案,使缩短开发周期,降低开发费用,提高抄表系统的稳定性和性价比成为可能。     

Acoustic emission from gas-filled coal under triaxial compression

Acoustic emission (AE) experiments have been performed on gas-saturated coal specimens under conventional triaxial compression. The AE characteristics were investigated for a methane gas flow through the coal specimen. One AE parameter, AE count, when normalized by the total count number was used to represent the damage evolution in the gassy coal. It is shown that this AE parameter is a reasonable indicator for damage occurring within the coal specimen since its envelope has almost the same shape as the complete stress–strain curve, except for a short time delay. In addition, the change in AE count is highly consistent with the change in coal permeability. Test results also show that methane containing coal emits a small number of AE events before entering the yield stage. AE activity gradually increases during the yield process up to the peak stress. The lowest permeability corresponds to the highest AE activity, implying failure will soon occur. An AE based constitutive model was constructed and the theoretical results agree well with those of experiments.