基于PNDSC 的欠驱动AUV编队控制器设计

针对含有模型不确定与未知海洋环境扰动下的欠驱动自主水下航行器(AUV)的编队控制问题, 提出一种基于预估器的神经网络动态面(PNDSC) 控制算法. 将动态面法引入控制器的设计中, 采用神经网络逼近AUV模型中的不确定项与海洋环境的扰动, 并结合预估器设计了神经网络权值的离散迭代更新率. Lyapunov 稳定性分析表明, 闭环系统所有信号是一致最终有界的. 仿真结果验证了所提出方法的有效性.

     

Pseudo‐predictor feedback control of discrete‐time linear systems with a single input delay

This paper studies the problems of stabilization of discrete‐time linear systems with a single input delay. By developing the methodology of pseudo‐predictor feedback, which uses the (artificial) closed‐loop system dynamics to predict the future state, memoryless state feedback control laws are constructed to solve the problem. Necessary and sufficient conditions are obtained to guarantee the stability of the closed‐loop system in terms of the stability of a class‐difference equations. It is also shown that the proposed controller achieves semi‐global stabilization of the system if its actuator is subject to either magnitude saturation or energy constraints under the condition that the open‐loop system is only polynomially unstable. Numerical examples have been worked out to illustrate the effectiveness of the proposed approaches. Copyright © 2015 John Wiley & Sons, Ltd.     

On input‐to‐state stability‐based design for leader/follower formation control with measurement delays

This paper addresses the design of low‐level controllers for leader–follower formations of nonholonomic vehicles in the presence of bounded measurement delays. The concept of input‐to‐state stability is extended to encompass the effect of bounded delays and restrictions on the input. A method is proposed to integrate a Smith predictor in a backstepping design on the basis of nested saturations and nonlinear small‐gain assignment, which allows for time delays in the feedback loop. Robustness analysis under uncertain bounded time delays is provided, and design tradeoffs resulting from the use of bounded controls are discussed. Illustrative simulations are shown to validate the design and robustness analysis in the context of a simple leader–follower trailing control problem. Copyright © 2012 John Wiley & Sons, Ltd.     

A neural network-based approach for dynamic quality prediction in a plastic injection molding process

This paper presents an innovative neural network-based quality prediction system for a plastic injection molding process. A self-organizing map plus a back-propagation neural network (SOM-BPNN) model is proposed for creating a dynamic quality predictor. Three SOM-based dynamic extraction parameters with six manufacturing process parameters and one level of product quality were dedicated to training and testing the proposed system. In addition, Taguchi’s parameter design method was also applied to enhance the neural network performance. For comparison, an additional back-propagation neural network (BPNN) model was constructed for which six process parameters were used for training and testing. The training and testing data for the two models respectively consisted of 120 and 40 samples. Experimental results showed that such a SOM-BPNN-based model can accurately predict the product quality (weight) and can likely be used for various practical applications.     

基于模型参考自适应Smith预估器的反馈式AGC厚度控制系统

针对具有纯时间延迟特性的反馈式AGC(automatic gauge contro1)系统,利用Smith预估器对纯时间延迟具有补偿作用的原理,建立了模型参考白适应Smith预估器反馈式AGC控制系统模型,给出了控制系统结构.推导了自适应调节律和设计算法,结合预估器模型,计算得到轧件出口厚度偏差值的表达式.仿真结果表明,模型参考自适应Smith预估器反馈式AGC系统对铝薄板带材轧制出口厚度偏差控制具有很好的控制效果,解决了反馈式AGC厚度控制由于纯时间延迟特性对控制性能产生很大影响的问题,消除了出口厚度波动现象,响应速度加快,可以满足高精度铝薄板带材轧制生产的控制要求.     

预估型氨法脱硫控制系统研究

燃煤发电系统中氨法脱硫控制系统具有时变、大延时、大惯性的特点。针对典型的大延迟系统,文中提出基于Smith预估器的脱硫控制系统,通过抵消系统被控对象中的纯滞后环节来提高系统的实时性。Smith预估器依赖准确的PID模型,系统中PID参数整定仍存在不确定性。利用SOA算法对PID参数进行整定,将绝对误差积分ITAE作为适应度函数,通过对适应度值的不断寻优,找到最佳的比例积分微分系数组合。仿真结果表明,相较于Smith预估器控制下的脱硫系统,基于SOA的Smith预估PID控制系统跟随性好且反应迅速,调节时间缩小为原来的9%,峰值时间缩小为原来的5%,具有较小的超调量,系统的实时性和稳定性得到保证。上述结果证明该算法对工程控制系统有效,并具有良好的应用前景。     

一类具有数据包丢失的长时延网络控制系统的分析与设计

针对一类网络控制系统,其网络诱导时延大于采样周期且存在数据丢包,研究了其稳定性和控制器的设计.在控制器端设计了一个状态预测器,其预测状态根据传感器的数据进行更新,然后用来确定控制作用.分析了预测误差的收敛性,证明了分离原理是成立的,并依据分离原理分别设计了状态预测器和控制器,给出了参数化设计方法.仿真例子验证了方法的有效性.     

带不确定噪声方差保性能鲁棒集中式融合Kalman 预报器

对于带不确定噪声方差的多传感器系统, 基于极大极小鲁棒估计原理, 提出保证估计性能的集中式融合鲁棒稳态Kalman 预报器. 对于预置的估计精度偏差指标, 利用Lagrange 乘数法求得相应噪声方差的最大扰动域, 使该域中所有可容许的噪声扰动, 其实际精度对鲁棒精度的偏差被保证在预置范围内, 并给出精度偏差的最大下界和最小上界. 应用Lyapunov 方程方法证明了保证估计性能能够被满足. 仿真分析表明了所得结果的正确性和有效性.

     

用于高速传感器的宽频差分50％占空比校正器

提出了一种用于高速传感器的宽带差分50％占空比校准电路。与传统CMOS模拟占空比校准电路相比,所提出电路结构简单工作稳定,并且证明了该电路的最高校正频率可达4GHz。所提出电路中的占空比检测器采用基于低通预滤波的连续时间积分器和带有源耦合逻辑结构的时钟缓冲器链。采用了0.18μmCMOS工艺,并针对高速应用条件进行了优化。实验结果表明,所提出电路在500MHz至4.0GHz频率范围内正常,可接受的输入占空比为30％?70％。在4GHz输入信号条件下功耗为5.37mW,输出抖动为19.3ps。测试芯片面积为550μm×370μm。     

基于日志分析的超级计算机错误预测方法研究*

大量的错误严重影响了超级计算机系统的稳定性,错误预测对于提高其稳定性有重要作用,日志分析是进行错误预测的有效方法.建立了错误预测的基本框架,包括日志的预处理、基础预测器和联合预测器,其中基础预测器包括时间预测器和关联预测器.在BlueGene/L日志上进行的实验结果显示联合预测器的预测效果比基础预测器好.这表明错误预测...