嵌入式视频网络控制器设计与实现

随着视频监控系统数字化、网络化和智能化的不断发展,其核心部件视频网络控制器的性能需求也越来越高。在此结合嵌入式软、硬件技术,基于PC-104硬件平台,采用定制嵌入式Linux操作系统,在Eclipse开发环境下进行软件开发,设计并实现了嵌入式视频网络控制器。采用面向对象编程思想,实现了为各类设备提供统一接口。能够为视频监控系统提供一种高可靠、低成本、小体积、低功耗、通用并可扩展的智能产品。经实际项目应用表明,该设备能够满足不同种类、不同厂家视频设备的互连互控,具有较高性能指标,非常适合轨道交通视频监控等领域。     

Analogue implementation of a neural network controller for UPSinverter applications

An analogue neural-network controller for UPS inverter applications is presented. The proposed neural-network controller is trained off-line using patterns obtained from a simulated controller, which had an idealized load-current-reference. Simulation results show that the proposed neural-network controller can achieve low total harmonic distortion under nonlinear loading condition and good dynamic responses under transient loading condition. To verify the performance of the proposed NN controller, a hardware inverter with an analogue neural network (NN) controller (using mainly operational amplifiers and resistors) is built. Additionally, for comparison purposes, a PI controller with optimized parameters is built. Experimental results confirm the simulation results and show the superior performance of the NN controller especially under rectifier-type loading condition. Implementing the analogue neural-network controller using programmable integrated circuits is also discussed     

网络危险数据细分控制器的设计与实现

受到步进电机低频共振特性的影响,导致以往设计的网络危险数据控制器的控制效率和控制精确度都较低。因此,设计网络危险数据细分控制器。网络数据传入控制器中的步进电机后会产生电流波动,A4988细分芯片对该电流进行细分控制。电源模块为A4988细分芯片的控制工作提供电压转换,维持细分芯片在标准电压下的正常工作。数据筛选模块包括收发电路和分类电路,收发电路对经A4988细分芯片控制后的网络数据进行接收,分类电路将其中的危险数据筛选出来,再经由收发电路传输给使用者。软件构建步进电机对网络数据的细分控制模型,实现控制器的高效、精准控制。实验结果表明,所设计的控制器具有较高的控制效率和控制精确度。     

Adaptive backstepping control using recurrent neural network forlinear induction motor drive

An adaptive backstepping control system using a recurrent neural network (RNN) is proposed to control the mover position of a linear induction motor (LIM) drive to compensate the uncertainties including the friction force in this paper. First, the dynamic model of an indirect field-oriented LIM drive is derived. Then, a backstepping approach is proposed to compensate the uncertainties including the friction force occurred in the motion control system. With the proposed backstepping control system, the mover position of the LIM drive possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic reference trajectories. Moreover, to further increase the robustness of the LIM drive, an RNN uncertainty observer is proposed to estimate the required lumped uncertainty in the backstepping control system. In addition, an online parameter training methodology, which is derived using the gradient-descent method, is proposed to increase the learning capability of the RNN. The effectiveness of the proposed control scheme is verified by both the simulated and experimental results     

基于机器学习的网络稳定控制器设计与实现

由于网络数据多元化以及网络非法入侵的干扰,当前设计出的网络稳定控制器往往响应时间过长,提出基于机器学习的网络稳定控制器设计方法。设计的控制器主要由开发板、控制电路和机器学习模块组成。机器学习模块利用特定的学习方式对网络被控对象进行监督,监督结果将被传送到控制电路进行多种学习行为的虚拟控制。开发板对虚拟控制结果进行接收,筛选出对网络被控对象的最优控制策略。机器学习模块对最优控制策略进行评价后,向网络被控对象实施稳定控制。实验结论证明,所设计的控制器可在维持对网络有效控制的同时,获取优异响应时间,响应能力较强,可较好地对设计目标进行实现。     

蜂窝网络信道分配均衡化控制器的设计与实现

当前的蜂窝网络中,移动具有随机特征,使得蜂窝网络信道到达率、业务应用类型等都具有随机性,导致部分蜂窝网络信道负载过大,资源均衡性较差的缺陷。因此,依据分层架构和模块化思想,设计并实现蜂窝网络信道分配均衡化控制器,其包括应用层、控制层以及基础设施层。控制器的基础模块和应用模块协同运行,实现网络信道资源的均衡分配,控制器通过Open Flow协议控制下的南向接口,同底层网络设备交流信息。蜂窝网络信道业务通过REST接口将资源申请命令反馈给控制器,促使控制器管理底层设备完成资源数据的转发,确保信道资源分配的均衡化。实验结果表明,所设计控制器下的网络信道吞吐量、平均系统公平性指数、用户平均中断概率以及信道负载率四个指标都较优秀,取得了令人满意的结果。     

智能门禁控制器的设计与实现

门禁控制器是门禁控制系统的核心,开发周期长,通用性差。在此利用现有读卡设备实现门禁控制器的设计,用户只需选用不同的读卡设备就可以实现不同卡的读取,对软件做适当修改,以满足不同门禁系统的需求,缩短了开发周期,提高了门禁控制器的通用性。在此还提供了多种开锁方式,方便用户的进出。在小区门禁系统中的应用证明,该门禁控制器运行稳定,可靠性高。     

A hybrid computed torque controller using fuzzy neural network formotor-quick-return servo mechanism

The dynamic response of a hybrid computed torque controlled quick-return mechanism, which is driven by a permanent magnet (PM) synchronous servo motor, is described in this paper. The crank and disk of the quick-return mechanism are assumed to be rigid. First, Hamilton's principle and Lagrange multiplier method are applied to formulate the mathematical model of motion. Then, based on the principle of computed torque control, a position controller is designed to control the position of a slider of the motor-quick-return servo mechanism. In addition, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a fuzzy neural network (FNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Moreover, a hybrid control system, which combines the computed torque controller, the FNN uncertainty observer, and a compensated controller, is developed based on Lyapunov stability to control the motor-quick-return servo mechanism. The computed torque controller with FNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rule numbers of the FNN. Finally, simulated and experimental results due to periodic step and sinusoidal commands show that the dynamic behaviors of the proposed hybrid computed torque control system are robust with regard to parametric variations and external disturbances     

Neural network implementation of a fuzzy logic controller

Fuzzy logic is an attractive technique for plant control but suffers from a heavy computation burden. A solution to this problem is proposed here and consists of implementing a fuzzy logic controller in a neural network. The solution is applied to the speed control of a DC motor drive and is validated by experimental results     

Adaptive neural network based controller for robots

A new Adaptive Neural Network (ANN) controller for robot trajectory trackingproblem is developed. A novel and efficient training algorithm for the proposed controller ispresented in this paper. The proposed training algorithm is based on updating the weights of thenetwork each step by minimizing the quadrant tracking errors and their derivatives.A simulation study is carried out on a polar robot manipulator to assure the effectivenessof the proposed trajectory tracking robot control system. The effects of the new controllerparameters and noisy external load disturbances on the control performance are studied. Thesimulation results of the proposed adaptive ANN controller are compared with those of aconventional ANN controller. The obtained results assured the robustness of the proposed ANNcontroller for: (i) uncertainties of the robot arm dynamic model and/or parameters, (ii) variousnoisy external load disturbances. Also, the simulation results assure the effectiveness of theproposed adaptive ANN controller against the conventional ANN one.     

无人机模糊小波神经网络轨迹线性化控制

针对系统存在不确定和有界干扰的情况,提出了一种基于模糊小波神经网络的轨迹线性化控制方法。利用模糊小波神经网络对非线性函数的逼近能力,减小不确定干扰对系统的影响,并与轨迹线性化方法结合设计了无人机飞控系统控制器。采用Lyapunov稳定性理论,证明了在所设计的控制器下,闭环系统所有信号一致最终有界。最后对系统存在不确定的情况下进行了仿真,并与没有加模糊小波神经网络的轨迹线性化控制器进行了对比,仿真结果证明了所提方法的有效性和鲁棒性。     

An implementation of a direction-finding antenna for mobilecommunications using a neural network

Direction-finding systems for radio signals are mostly used in mobile communications and avionics applications for antenna tracking or navigation purposes. In general, such systems require accurate calibration and may be sensitive to noise and external interference. In this paper, we investigate the performance of a neural network-based direction-finding system under such conditions. The proposed topology is a hybrid one, combining a simple RF signal beamformer with a neural network. The training of the neural network is accomplished experimentally with a three-element antenna array by varying the beam's direction and the carrier frequency. The error on the estimated direction of arrival caused by the environment and training limitations are investigated     

智能电动阀门控制器的设计与实现

为了保障阀门工作的安全性和可靠性,智能控制系统由控制器和执行器两部分组成。控制器作为智能化控制的核心组成部分,它以AVRmega系列的mega128和mega16单片机为基础,利用霍尔传感器监控阀门位移,并与预定值进行比较实现阀门位移的闭环控制,同时通过应力传感器和温度传感器实现三相电机的过力矩保护和过温保护。系统三相电源自动相序检测和纠正功能,可以使电机运行不受电源接线的影响。在比较危险或者需要远程控制的场合,系统的最终目标生成的控制信号,能够保证控制器安全有效的运行。     

Design and implementation of H-inf controller for micro-monocopter

An all rotating platform has been modified with the purpose of having at one's disposal an operative monocopter. The nature of the modifications are described, as well as the control strategy designed and implemented to control the prototype. This strategy corresponds to a H-inf controller in which a nonlinear function has been included to cancel the propeller quadratic force.     

一种STN LCD控制器的设计及其实现

介绍了一种超扭曲向量(STN)LCD控制器的设计方案,详细分析了该控制器各模块的划分及其功能,用Verilog硬件描述语言完成了整个LCD控制器的设计工作,并用Cadence Verilog-XL软件对设计结果进行了仿真验证.仿真结果表明该LCD控制器实现了预定的设计目标.     

权重连接神经网络的光电实现

在Ｈｏｐｆｉｅｌｄ模型基础上，对具有权重连接的Ｈｏｐｆｉｅｌｄ模型引入连接权重矩阵，这样只要在Ｈｏｐｆｉｅｌｄ内容寻址记忆光电阵更前多加一个连接权重矩阵阵列，则得具有权重连接的神经网络模型的光电实现。     

基于BP神经网络的智慧社区综合平台的设计

为改善现有社区建设缺乏统一的综合服务平台、功能和技术的可扩展性差、无法满足用户复杂的业务需求等不足之处,实现多小区、多物业、多商户扩展的架构,建立集电子政务、数字物管、在线电商于一体的社区商圈,文中提出了一种新型的智慧社区O2O综合服务平台,采用账户+小区+角色+权限的四重方式实现对复杂角色权限的管理来增强系统的安全性和可扩展性;以账户体系、基础物业服务、社区商业服务三个方面为切入点,构建统一的可扩展的社区综合服务平台,实现真正意义上的以500米为半径的线上生活圈;并结合BP(Back Propagation)神经网络算法实现业主对商家评分功能,使评价系统能够根据客观环境自适应调节,减少人为因素对商家评价的主观影响,从而保障社区商户信誉度的真实性和可靠性,为业主提供优质的网购服务。     

OBS核心控制器结构设计与硬件化实现

设计了一个基于JIT协议的OBS核心控制器,该控制器将路由选择和信道调度整合在一个模块中处理,并采用信道资源信息共享与先调度再转发的处理机制,简化了控制器的结构,有效提高了OBS核心节点的处理速度,同时也避免了路由选择的盲目性,减少丢包。在FPGA平台上实现了提出的OBS核心控制器结构并进行了实际测试。测试结果表明：接收完BCP包到发出光开关设置信号的最短时间为100ns。     

塞拉门控制器引导程序的设计与实现

Bootloader程序在嵌入式系统中应用广泛。当系统需要软件升级或软件中存在BUG时,可以方便地实现程序的在线编程和数据更新,文中研究了基于飞思卡尔Kinetis系列32位微控制器K60,设计了基于三种通信方式的Bootloader程序。分别实现微控制器通过UART,以太网,CAN总线下载程序,这三种方式都是基于FC协议实现PC机与微控制器间的通信,实验结果表明,三种通信方式都可以实现微控制器程序的下载。