基于RBF神经网络整定PID的电液比例系统位置控制研究

针对凿岩机械臂的电液比例系统位置控制精度问题,提出了一种基于径向基函数(RBF)神经网络整定PID的电液比例系统位置控制方法。首先,在AMESim中搭建了阀控非对称液压缸的电液比例系统简化模型,设置了各个模块的参数;然后,利用MATLAB/Simulink搭建了系统闭环控制模型,通过不断更新RBF网络模型并修正PID参数,实现了基于RBF神经网络整定PID的电液比例系统位置控制目的;结合AMESim搭建的电液比例系统模型和Simulink下搭建的控制器进行了联合仿真;最后,基于凿岩台车机械臂实验平台,进行了电液比例系统位置控制实验。仿真结果表明:在受到外部干扰的情况下,RBF神经网络整定PID控制系统能够在0.3 s内控制活塞杆重新运行至目标位置,平均响应时间为1.5 s,位置精度误差不超过5 mm。实验结果表明:与常规PID控制方法相比,RBF神经网络整定PID控制活塞杆位置精度误差降低了75%,位置精度误差在工程实际要求的10 mm范围以内,因此,RBF神经网络整定PID算法可以有效提高电液比例系统的位置控制精度,满足凿岩机械臂实际工作中对电液比例系统位置精度的控制要求。

基于RBF神经网络PID算法的锅炉水温控制与研究

针对过程控制实验中水温控制的PID算法参数难以整定的问题,提出了一种基于径向基函数(Radial Basis Function,RBF)神经网络整定PID的算法,并以仿真与实验相结合的方式应用于水温控制实验中。通过使用阶跃响应曲线法辨识锅炉水温数学模型;设计用RBF神经网络整定PID参数的方法,针对对象模型进行仿真;最后将整定的PID参数应用于水温控制实验验证,并与常规PID方法进行实验比较。结果表明,RBF神经网络整定PID控制器的控制方法具有更好的鲁棒性和自适应性,能取得良好的控制效果。

基于神经网络整定的圆锥破碎机控制系统的模糊预估控制

针对圆锥破碎机,本文提出一种基于神经网络整定的模糊预估控制,神经网络能够动态调整PID控制器的三个参数kp、ki、kd。文中对基本模糊控制器和整定PID控制器参数的神经网络分别进行了设计,并进行仿真研究,结果表明该控制方案能提高系统的动态和稳态性能。

基于SIMULINK的网络先进控制系统仿真及研究

利用MATLAB/SIMULINK对以神经网络整定的网络先进控制系统进行了仿真,仿真对象采用的是ALSTOM提出的BENCHMARK CHALLENGE II中的汽化器模型,从仿真结果可以看出基于神经网络整定PI的控制器有较好的控制效果,但是网络诱导延时的引入对神经网络调节PI参数会造成较大影响,甚至导致系统不稳定。最后,文章提出了一种采用抛物线法预测误差的补偿策略,仿真结果表明了该补偿策略对保证系统稳定的有效性。

论网络环境下图书馆的信息服务工作

探讨了网络环境对图书馆信息服务工作的巨大影响 ,分析了网络信息服务的局限性及图书馆参与网络竞争的优势 。

“干部网络学习在线”的平台研究

本文首先对"干部网络学习在线"的平台的特点进行分析,最后有针对性地提出对适合学院的"干部网络学习在线"平台三种架构进行研究和分析。

REGULARIZATION APPROACH FOR FAST INTEGER AMBIGUITY RESOLUTION OF MEDIUM-LONG BASELINE GPS NETWORK RTK

An improved method based on the Tikhonov regularization principle and the precisely known reference station coordinate is proposed to design the regularized matrix. The ill-conditioning of the normal matrix can be improved by the regularized matrix. The relative floating ambiguity can be computed only by using the data of several epochs. Combined with the LAMBDA method, the new approach can correctly and quickly fix the integer ambiguity and the success rate is 100% in experiments. Through using measured data sets from four mediumlong baselines, the new method can obtain exact ambiguities only by the Ll-frequency data of three epochs. Compared with the existing methods, the improved method can solve the ambiguities of the medium-long baseline GPS network RTK only using L1-frequency GPS data.

基于旋转坐标变换交流电子负载模拟实验研究

针对传统交流电子负载基于内环电流PI控制动态响应较差,且易受网侧波动干扰,以双PWM变换器为电路基础,参考三相PWM整流器通过旋转坐标变换分别控制有功与无功电流来消除稳态误差的模型,提出单相PWM整流器(VSR)旋转坐标变换模型。通过构建正交虚拟电流与前馈解耦并结合基于BP神经网络的自调整PI控制,在稳定直流母线电压的同时实现负载模拟电流的矢量控制,提高负载模拟的动态和稳态特性。实验结果表明,在纯阻、感阻、容阻负载模拟下,该控制策略能够有效提高负载模拟动态响应,对比常规PI,可知基于BP神经网络自整定的PI控制在参考电流为1 A阶跃响应中超调量减少约10%,调节时间减少约9 ms。

HBO的成功对中国电视收费频道运营的启示

《HBO的成功对中国电视收费频道运营的启示》一文,介绍了美国目前最赚钱的付费电视网HBO的成功经验:受众为本的传播理念、高效的运营模式、质量意识、品牌意识等,并提出了中国电视收费频道应该从中受到哪些启示。文章对正在进行电视付费频道建设的中国电视人有较强的启发和借鉴意义。

6-DOF摆台多系统联合仿真与实验研究

六自由度并联液压摇摆台(6-DOF)在模拟船舶受海浪扰动的运动中发挥重要作用,为改善6-DOF控制性能,将6-DOF的机械、液压和控制系统有机结合起来联合仿真,并针对6-DOF本身强耦合、多变量的特点,将BP神经网络整定PID控制策略应用到6-DOF联合仿真中,最终在6-DOF上进行了验证实验。结果表明,联合仿真后开发的基于BP神经网络整定PID控制策略的6-DOF系统具有更好的跟随特性。显示出综合了各软件优点的联合仿真方法所建立的控制系统模型,能够充分考虑系统的机械运动动态特性与液压控制系统的随动特性,能够对机电液系统的工作过程进行更为精准的控制,具有建模精度高的优点,对6-DOF系统优化具有重要的参考价值。

Parallel Implementation of Global Illumination Using PVM

In this paper an attempt of employing network resources to solve a complex and time-consuming problem is presented. The global illumination problem is selected as the study objective. An improved density estimation algorithm is first developed, in which the more inherent concurrency is explored. Then its parallel implementation by using a PVM mechanism and the running performance analysis are provided. The analysis results show the expected speed-up obtained and demonstrate that the PVM has good application prospects for parallel computation in a distributed network.

光电跟踪测试仪的设计

文章以线性化的光电跟瞄平台为研究对象,采用双闭环控制以提高光电跟瞄平台的跟踪精确度,内环采用输出反馈 H ∞控制,外环采用神经网络 PID 控制,同时外环采用 Smith 预估器对视频跟踪引起的纯滞后进行补偿,仿真结果表明,与经典 PID 控制相比,前者的抗干扰性较好,满足跟踪精度要求。

半桥逆变型磁共振式无线充电系统建模与控制

针对半桥谐振逆变型磁共振式无线充电(MCR-WCT)系统工作状态模糊、高阶非线性、控制理论不成熟等问题,在建立半桥谐振逆变电路等效模型的基础上,采用广义状态空间平均法(GSSA)对MCR-WCT系统进行大信号和小信号建模,在GSSA模型的基础上设计电流单闭环控制器,制定基于BP神经网络的自整定PID控制策略。最后,通过Matlab编程对GSSA大信号模型进行暂态和稳态分析,对比Simulink模型仿真结果验证GSSA模型的可行性;通过Matlab仿真对比经典PID控制和BP神经网络自整定PID控制策略,在电流设定值为1 A的阶跃响应中,BP神经网络自整定PID控制在0.25 ms内达到稳态,稳态误差在2%内,最大超调量只有5%,相比经典PID控制具有更好的动静态性能。

Airflow adjustment and minimization of the air power of ventilation network

It is often required to know which roadway （adjustment roadway） resistances and how much values of the resis- tances should be changed to make the airflow rates in roadways （target roadways） to certain required values in the practice of mine ventilation. In this case, the airflow rates of the target roadways and the resistances of the roadways other than the ad- justment roadways are the given conditions and the resistances of the adjustment roadways are the solutions to be found. No straightforward method to solve the problem has been found up to now. Therefore, trial and error method using the ventilation network analysis program is utilized to solve the problem so far. The method takes long calculation time and the best answer is not necessarily obtained. The authors newly defined ＂airflow element＂ as an element of the ventilation network analysis. The resistances that satisfy the airflow requirements can be calculated straight forwardly by putting the function of the airflow element into the ventilation network analysis. The air power required for the ventilation can be minimized while meeting the airflow requirements by the advanced application of the method. The authors made the computer program fulfill the method. The program was applied to actual ventilation network and it was found that the method is very practical and the time required for the analysis is short.

Design and Implementation of an Adaptive Feedback Queue Algorithm over Open Flow Networks

The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service(QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback(PPMF) queues based on software defined networks(SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35--80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.

Green Networking Based Energy Efficient Communications

The mainstream approaches to green networking are discussed first from the view of engineering,including resource consolidation,server virtualization,selective connectedness,and proportional computing.A brief introduction to network virtualization techniques is given then and a virtual node embedding approach is provided.Finally,three kinds of enhanced green networking schemes by network virtualization are proposed,that is enhancement to sever virtualization,resource consolidation and Adaptive Link Rate(ALR).Examples are included to show the virtue of network virtualization to green networking in terms of energy efficient communications.

Time series ground subsidence inversion in mining area based on CRInSAR and PSInSAR integration

The subsidence of the mining area was monitored by analyzing the phase of permanent scatters （PS） which maintained high coherence in magnitude of SAR images.A hew method of spatial unwrapping was presented which used the subsidence rates calculated on comer reflector （CR） points as constraints for PS network to perform the spatial unwrapping using the parametric adjustment method.The algorithm achieved the integration of CR data and PSInSAR algorithm.The colliery dense distributed area around Baisha reservoir was chosen as the study area in the experiment.The time series of subsidence from February in 2007 to February in 2010 is successfully inversed by using the periodic function to simulate the linear and nonlinear components of the deformation.The simulation results show that the accuracy can be ± 2.1 mm with the leveling data being used as the external validation data.

Synthesis and Scheduling of Optimal Batch Water-recycle Networks

This work develops an optimization-based methodology for the design and scheduling of batch water recycle networks. This task requires the identification of network configuration, fresh-water usage, recycle assignments from sources to sinks, wastewater discharge, and a scheduling scheme. A new source-tank-sink representation is developed to allow for storage and dispatch tanks. The problem is solved in stages by first eliminating scheduling constraints and determining minimum usage of fresh water and wastewater discharge. An iterative procedure is formulated to minimize the total annual cost of the system by trading off capital versus operating costs. The work overcomes limitations in previous literature work including restricted recycle within the same cycle, lumped balances that may not lead to feasible solutions, and unrealistic objective functions. A case study is solved to illustrate the usefulness of the devised procedure.

CONSTRUCTION OF THE ENCRYPTION MATRIX BASED ON CHEBYSHEV CHAOTIC NEURAL NETWORKS

The paper proposes a novel algorithm to get the encryption matrix. Firstly, a chaotic sequence generated by Chebyshev chaotic neural networks is converted into a series of low-order integer matrices from which available encryption matrices are selected. Then, a higher order encryption matrix relating real world application is constructed by means of tensor production method based on selected encryption matrices. The results show that the proposed algorithm can produce a "one-time pad cipher" encryption matrix with high security; and the encryption results have good chaos and auto-correlation with the natural frequency of the plaintext being hidden and homogenized.

A Methodology for Bridge Condition Evaluation

Due to the substantial role of bridges in transportation networks and in accordance with the limited funding for bridge management, remediation strategies have to be prioritised. A conservative bridge assessment will result in unnecessary actions, such as costly bridge strengthening or repairs. On the other hand, any bridge maintenance negligence and delayed actions may lead to heavy future costs or degraded assets. The accuracy of decisions developed by any manager or bridge engineer relies on the accuracy of the bridge condition assessment which emanates from visual inspection. Many bridge rating systems are based on a very subjective procedure and are associated with uncertainty and personal bias. The developing condition rating method described herein is an important step in adding more holism and objectivity to the current approaches. Structural importance and material vulnerability are the two main factors that should be considered in the evaluation of element structural index and the causal factor as the representative of age, environment, road class and inspection is implemented as a coefficient to the OSCI （overall structural condition index）. The AHP （analytical hierarchy process） has been applied to evaluate the priority vector of the causal parameters.