一类非线性随机时滞系统的故障诊断

针对一类非线性随机时滞系统提出了一种新的故障检测算法,该方法不同于传统的故障检测方法,是通过构建一种带有Consensus滤波器的故障诊断滤波器的方法来进行故障诊断.首先采用一组传感器测量系统实际输出,然后根据传感器的测量值构建一组残差生成器,将每个残差生成器看作一个小世界网络模型中的一个节点,采用动态Consensus算法计算出残差生成器的残差,并根据残差来判断系统是否有故障发生.仿真结果表明了本文所提出方法的可行性和有效性.     

Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

基于GP2Y0A02距离测量的仿真与辅助设计

为了实现非接触距离测量,利用多个仿真与设计软件设计了采用GP2Y0A02模块的距离光学测试系统。在PROTEUS中测量GP2Y0A02电压值,并在Matlab中采用多元线性回归建立GP2Y0A02电压与距离的拟合曲线,最后在开发的测量程序中利用拟合曲线求解得到距离量。测试结果表明,对于非线性位置测量采用适当数据处理方法能得到满意的测量精度。     

Integrated Game Based Guidance with Nonlinear Autopilot Design for Maneuvering Target Interception

The integrated game theory based guidance law with nonlinear autopilot (GGNA) system is presented in this paper. The guidance law is designed based on linear differential game theory while considering the motion of the target in 3‐D space such that the distance between the missile and the target is minimized faster than before. The autopilot system based on quaternion representation is developed using sliding mode control method to generate the attitude command. The stability of the integrated guidance and nonlinear autopilot system is analyzed with Lyapunov stability theory. In addition, this research assumes wingless missiles in our context in order to reduce the nonlinear effect from the aerodynamics. Furthermore, in order to extend the operation range of missiles from endo‐atmosphere to exo‐atmosphere, the missiles are equipped with Thrust Vector Control (TVC) mechanisms and Divert Control System (DCS). Finally, extensive simulations incorporating aerodynamic models are demonstrated to verify the validity of the proposed integrated guidance/autopilot systems. Moreover, the simulation results reveal that the mission of intercepting a maneuvering target is successfully accomplished.     

Non‐Parametric Identification Method of Volterra Kernels for Nonlinear Systems Excited by Multitone Signal

To solve the problem of Volterra frequency‐domain kernels (VFKs) of nonlinear systems, which can be difficult to identify, we propose a novel non‐parametric identification method based on multitone excitation. First, we have studied the output properties of VFKs of nonlinear systems excited by the multitone signal, and derived a formula for identifying VFKs. Second, to improve the efficiency of the non‐parametric identification method, we suggest an increase in the number of tones for multitone excitation to simultaneously identify multi‐point VFKs with one excitation. We also propose an algorithm for searching the frequency base of multitone excitation. Finally, we use the interpolation method to separate every order output of VFK and extract its output frequency components, then use the derived formula to calculate the VFKs. The theoretical analysis and simulation results indicate that the non‐parametric method has a high precision and convenience of operation, improving the conventional methods, which have the defects of being unable to precisely identify VFKs and identification results are limited to three‐order VFK.     

An Adaptive and Optimized Switching Observer for Sensorless Control of an Electromagnetic Valve Actuator in Camless Internal Combustion Engines

In this paper, the design and operation of a special electromagnetic actuator as a variable engine valve actuator are presented. Further, this paper describes a feasible approximated velocity switching estimator based on measurements of current and input voltage to achieve sensorless control. The proposed concept allows a reduced‐order observer to be conceived and yields a specific control strategy with an acceptable performance. In general, this approach represents a viable strategy to build reduced‐order observers for estimating the velocity of systems through the measurement of input current and voltage. The robustness of the velocity tracking is explored using a minimum variance approach. The effect of the noise is minimized, and the position can be achieved through an adaptive and optimized structure by combining this particular velocity estimator and an observer based on the electromechanical system. Position control is achieved through an inversion of the model. This approach avoids a more complex structure for the observer and yields an acceptable performance as well as eliminating bulky position‐sensor systems. In addition, a control strategy is presented and discussed. Computer simulations of the sensorless control structure are presented in which the positive effects of the observer with optimized parameter setting are visible in the closed‐loop control.     

不确定切换时滞非线性系统状态切换的指数稳定性

利用状态依赖控制策略对切换信号进行设计,使得一类参数不确定时滞非线性切换系统指数稳定且具有一定的??∞抗干扰性能。利用Lyapunov-Krasovskii (LK)函数方法,以线性矩阵不等式组的方式,给出了稳定切换律存在的充分条件,并且该系统是指数稳定的。通过引入自由矩阵并结合积分不等式技巧,得到了保守性较低的稳定性条件。仿真算例表明了所提出方法的有效性和较低的保守性。     

非线性PID自学习控制方法研究

针对非线性、多变量、强耦合系统的控制问题,提出一种基于双曲函数的非线性PID自学习控制方法。在PID控制过程中,用双曲函数构造比例、积分、微分3个增益参数分别随误差变化的规律曲线,将传统线性PID控制律转化为非线性PID控制律的控制思想,并使用自学习算法实时调整3个非线性增益函数的增益系数,实现基于双曲函数的非线性PID自学习控制。仿真实验结果表明,与其他控制方法相比,该方法具有更强的鲁棒稳定性和抗扰动能力,是一种有效的控制方法,在非线性控制领域具有重要的应用价值。     

一种瓦斯涌出量系统预测辨识模型的研究

针对煤与瓦斯突出灾害中瓦斯涌出量的辨识预测问题,结合采煤工作面瓦斯涌出量系统的现场实际特点,提出了混沌免疫遗传优化算法(CIGOA)与Elman神经网络相结合的耦合算法(CIGOA-ENN)。利用GIGOA的全局寻优能力替代梯度下降法,以克服Elman神经网络固有的缺陷。并根据输入的数据,构造基于CIGOA和ENN耦合算法的瓦斯涌出量系统辨识预测模型。利用矿区采集的现场监测数据进行仿真预测,实验表明该预测模型与BPNN,GA-ENN等神经网络预测模型相比,其收敛速度更快、收敛精度更高、鲁棒性更强,为解决煤矿瓦斯涌出量的预测问题提供了一个行之有效的方法。     

基于非线性关联维特征提取的机械自动化监测系统

提取天然气压缩机故障状态下振动信号的故障特征是设计机械自动化检测系统的核心技术。提出一种基于非线性关联维特征提取的机械自动化监测系统设计方法,在故障诊断原理基础上,进行故障振动信号时间序列分析,设计故障振动信号相空间重构方法,改进了相空间重构最佳时延和嵌入维数参数计算的关键技术,通过提取关联维故障特征,在Simulink平台上设计了自动化监测系统。系统实验结果表明,该算法和系统能使各类故障状态下提取的关联维特征的标准差显著性降低,特征分布聚类能力明显提高,系统能有效检测各类故障,实现了机械设备的自动化监测,在自动化故障诊断仪表设计等领域具有较好的工程实践价值。