应变式称重传感器的非线性校正

因受自身材质、工艺的限制以及外界环境影响,应变式称重传感器输入—输出特性存在非线性误差,影响系统测量精度,需要对其进行非线性校正。采用曲线拟合法建立传感器逆模型,并存储于单片机中用于非线性校正,结合外围硬件电路完成对被测数据的采集与实时处理。设计完成的测量系统具有一定的环境自适应性和智能化特点。实验结果表明,校正后系统的非线性和零点漂移得到明显改善,同时软、硬件相结合的设计方式具有较高的应用价值。     

基于相关向量机的MEMS陀螺仪随机漂移补偿

提出了一种基于相关向量机的MEMS陀螺仪随机漂移预测方法。针对MEMS陀螺仪随机漂移误差的非线性、不确定性等特点,建立了相关向量机预测模型,并采用EM算法获得模型的参数。针对随机漂移的混沌特性,利用相空间重构技术,将重构后的漂移序列作为输入变量进行模型的训练和预测。训练和测试结果均表明,该方法具有很好的预测效果,优于常用的时间序列分析法和支持向量机法。利用预测结果对随机漂移进行补偿,有效地提高了陀螺的使用精度。     

基于二元多项式拟合法的压力传感器输入信号重构

为了同时解决压力传感器输出特性的非线性和温度漂移问题,提出利用二元多项式根据传感器输出信号及其内部温度来重构被测压力.给出了被测压力重构模型的具体形式,以传感器静态特性标定试验数据为依据,利用最小二乘法求解模型系数矩阵,利用单点最大拟合误差、误差平方和模型阶次三项指标进行模型择优.基于重构模型给出了测量电路检测精度估算方法.本方法在传感器静态特性标定数据范围内得到了便于工程计算的一致表达式,同时解决了传感器的非线性和温度漂移两个主要问题,计算所用数据量大大小于插值法.某型硅谐振压力传感器的应用验证了本方法的合理性和有效性.     

考虑非线性项的卫星编队保持

针对低轨道运行的编队卫星在非线性项作用下,伴随卫星运行的相对运动轨道发生偏移的情况,传统的李亚普诺夫方法能较好地控制轨道的初始偏移,使系统达到李亚普诺夫大范围一致稳定,但长期项误差震荡较大.本文提出了一种多回路结构的卫星轨道保持的控制方法,内回路选取使系统满足李亚普诺夫大范围一致稳定的控制律,外回路选取LQR线性状态调节器.此内外回路调节器能更好地抑制环绕卫星相对于基准轨道的误差漂移,更好地稳定编队队形.最后,数值仿真结果验证了此方法比传统的李亚普诺夫方法具有使编队更稳定的效果.     

基于Z-力敏元件的测力研究

Z-力敏元件是一种新型的半导体器件,输出为与压力应变有一定对应关系的频率量,该器件具有分散性、非线性、温度特性、零点漂移等特性,须通过硬件或补偿软件才能实际应用。本文对Z-力敏元件的特性进行了研究,通过三次样条插值方法实现力敏元件的线性化,通过二次插值方法实现温度补偿,通过加载时重量突变编程锁定的方法解决零点漂移。实验表明,通过数字化补偿后Z-力敏元件可输出与被测压力应变成正比的线性输出,该研究为Z-力敏元件的实际应用奠定了基础。     

面向污水处理的动态变分贝叶斯混合因子故障诊断

在污水生化处理过程中,存在着多变量耦合、强非线性、参数时变、大滞后等特点,面对这些特点,传感器故障频发,从而导致生化过程无法得到有效优化和诊断.为此,本文在结合动态数据特性的基础上提出了一种基于变分贝叶斯混合因子的动态故障诊断方法,同时,利用混合因子的在线调整实现了诊断模型的半自适应化.该方法能够捕捉到污水处理过程的强非线性和动态性,从而可有效降低故障诊断的误报率和漏报率.通过在国际水协会的BSM1模型上的模拟研究,充分表明所提出的策略可以显著提高故障诊断能力,精确地检测传感器的突变和漂移故障,甚至定位故障所发生的根本原因.     

A comparison of simulated annealing and genetic algorithm for optimum design of nonlinear steel space frames

In this article, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames that are based on simulated annealing and genetic algorithm. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as the American Institute of Steel Construction (AISC) wide-flange shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraints for columns were imposed on frames. The algorithms were applied to the optimum design of three space frame structures, which have a very small amount of nonlinearity. The unconstrained form of objective function was applied in both optimum design algorithms, and constant penalty factors were used instead of gradually increasing ones. Although genetic algorithm took much less time to converge, the comparisons showed that the simulated annealing algorithm yielded better designs together with AISC-LRFD code specification.     

电容式薄膜真空压力传感器设计

为了满足在工程型号上的使用要求,解决真空压力传感器敏感探头壳体与传感器壳体隔离绝缘问题;传感器输出信号非线性的补偿问题;传感器热零点漂移的全电路的温度补偿问题,采用电容式薄膜封装结构,壳体为电容的另一极,在0.1~100 Pa的范围内进行了校准测试,实现了传感器0.2%FS的测量精度.     

压力传感器温漂及非线性校准技术研究

高精度压力传感器是航空领域应用非常广泛的传感器,常处于严苛的工作环境.为使压力传感器在特殊的测试环境中保持高测量精度,传感器的性能设计成为研究关键.合理的信号调理电路以及正确的误差校准原理,将显著提高传感器性能.通过在传感器的信号调理电路中使用可编程模拟信号调节器,对桥式压力敏感元件的温度漂移误差及非线性误差进行实时修正,使压力传感器实现了智能化自校准,有效提升了压力传感器的精度和环境适应性.     

倾角仪特性研究及其测量误差补偿

为了减轻非线性因素和环境温度的变化对倾角仪测量的影响,在充分研究倾角仪测量特性的基础上,采用多项式拟合方法研究了倾角仪非线性误差和温度漂移误差的软件补偿技术.建立了测量误差与非线性输出的多项式模型,拟合求出了多项式模型的各个系数与环境温度的关系函数,得到了倾角仪在一定倾角范围和温度范围内的测量误差的计算公式.实验证明了...     

离子迁移谱(IMS)技术中漂移管的多物理场仿真方法研究

漂移管是离子迁移谱(IMS)检测仪的核心部件,设计优劣直接影响IMS仪器的性能。离子在漂移管中的运动十分复杂,受电场及气流、温湿度、压强等多种环境因素的影响。为了研究离子在漂移管中的迁移过程,为IMS漂移管的设计和优化提供指导,本文建立了一种基于SIMION/SDS的多物理场仿真方法,综合考虑了电场、气流、温度及压强等因素的影响,模拟离子在漂移管中的运动。选择IMS标准剂进行实验测试,将仿真结果与实测的离子迁移谱图进行对比分析,验证该仿真方法的正确性。结果表明,漂移管的多物理场仿真方法能够有效地模拟多环境因素影响下离子在漂移管中的迁移情况,对漂移管的设计优化有着重要的意义。     

基于主要特征抽取的重现概念漂移处理算法

针对重现概念漂移检测中的概念表征和分类器选择问题,提出了一种适用于含重现概念漂移的数据流分类的算法——基于主要特征抽取的概念聚类和预测算法（Conceptual clustering and prediction through main feature extraction, MFCCP）。MFCCP通过计算不同批次样本的主要特征及影响因子的差异度以识别重复出现的概念,为每个概念维持且及时更新一个分类器,并依据Hoeffding不等式选择最合适的分类器对当前样本集实施分类,以 提高对概念漂移的反应能力。在3个数据集上的实验表明：MFCCP在含重现概念漂移的数据集上的分类准确率,对概念漂移的反应能力及对概念漂移检测的准确率均明显优于其他4种 对比算法,且MFCCP也适用于对不含重现概念漂移的数据流进行分类。     

高精度传感器弹性元件应变梯度的非线性误差分析

定量地分析了弹性元件应变梯度产生的非线性误差，通过分析计算表明弹性元件粘贴区的应变梯度是应变式高精度传感器非线性误差产生的主要因素之一。     

Decentralized intelligent tracking control for uncertain high‐order stochastic nonlinear strong interconnected systems in drift and diffusion terms

This paper focuses mainly on decentralized intelligent tracking control for a class of high‐order stochastic nonlinear systems with unknown strong interconnected nonlinearity in the drift and diffusion terms. For the control of uncertain high‐order nonlinear systems, the approximation capability of RBF neural networks is utilized to deal with the difficulties caused by completely unknown system dynamics and stochastic disturbances, and only one adaptive parameter is constructed to overcome the overparameterization problem. Then, to address the problem from high‐order strong interconnected nonlinearities in the drift and diffusion terms with full states of the overall system, by using the monotonically increasing property of the bounding functions, the variable separation technique is achieved. Lastly, based on the Lyapunov stability theory, a decentralized adaptive neural control method is proposed to reduce the number of online adaptive learning parameters. It is shown that, for bounded initial conditions, the designed controller can ensure the semiglobally uniformly ultimate boundedness of the solution of the closed‐loop system and make the tracking errors eventually converge to a small neighborhood around the origin. Two simulation examples including a practical example are used to further illustrate the effectiveness of the design method.     

海上自由物体漂移轨迹预测方法

为提高对海上遇险目标的搜索效率,在搜救行动开始前需要对搜索目标的位置进行预测.在获得遇险目标的最后告知位置后,计算漂流轨迹可以预测搜救力量展开搜索时险目标的实际位置.通过计算各环境因素带来的漂移速度分量,进行矢量合成后可以得到遇险目标的漂移速度.对搜索目标遇险后的漂移轨迹进行预测,以此划定搜索区域.     

自适应智能型积分器设计

传统模拟积分器由于运放和积分电容的不理想,存在着零点漂移、非线性误差以及泄漏等问题。而当积分时间不断增加时,积分漂移随之线性增加,并成为影响积分输出精度的重要因素之一。对此设计了自适应智能型积分器。主要思想：利用积分器前一次的漂移斜率来扣除本次的积分值,以达到减小漂移的目的。     

光纤陀螺环振动性能评价体系的建立与应用

建立了光纤环振动响应的理论模型,分析得到光纤环振动瞬态响应振幅与振动激励频率和加速度振幅呈正比的结论,并进行实验验证,以此为依据建立包括若干参数的光纤环振动性能全面评价体系,定量评价光纤环的振动性能。搭建光纤环振动性能测试系统,并对大量光纤环进行振动性能全面测试,振动灵敏度为1°/(h.Hz),非线性度为10%,重复性误差约为2%,振动致零偏漂移量级约为1°/h,证明了该评价系统对不同固胶光纤环有很好的区分度,能全面有效地反映光纤环的振动性能。     

Cone-bounded nonlinearities and mean-square bounds—Smoothing and prediction

Mean-square performance bounds are derived for smoothing and prediction problems associated with the broad class of nonlinear dynamic systems which, when modeled by Ito differential equations, contain drift (·dt) coefficients which are, to within a uniformly Lipschitz residual, jointly linear in the system state and externally applied control. Included in this paper are lower bounds on the error covariance attainable by any smoother or any predictor, including the optimum, and upper bounds on the performance of some simple, implementable predictors reminiscent of the designs which are optimal in the linear case. The lower bounds on smoothing and prediction performance are established using measure-transformation techniques to relate a version of the nonlinear problem to its linearization. The upper bound on prediction performance is constructed by a direct analysis of the estimation error. All the bounds hold for correlated system and observation noises. All are rigorously derived and independent of control or control law. In each case, the computational effort is comparable to that for the corresponding optimum linear smoothing or prediction problem. The bounds converge with vanishing nonlinearity (vanishing Lipschitz constants) to the known optimum performance for the limiting linear system. Consequently, the bounds are asymptotically tight and the simple designs studied are asymptotically optimal with vanishing nonlinearity.     

Adaptive stabilization of uncertain nonholonomic systems by state and output feedback

In this paper, adaptive state feedback and output feedback control strategies are presented for a class of nonholonomic systems in chained form with drift nonlinearity and parametric uncertainties. Both control laws are developed using state scaling and backstepping techniques. In particular, novel adaptive switching is proposed to overcome the uncontrollablity problem associated with x₀(t₀)=0. Observer-based output feedback design is developed when only partial system states are measurable, and a filtered observer rather than the traditional linear observer is used to handle the technical problem due to the presence of unavailable states in the regressor matrix. The proposed control strategies can steer the system globally converge to the origin, while the estimated parameters maintain bounded.     

基于关联向量机的混沌时间序列预测

混沌是一种貌似无规则的运动,指在确定的系统中,不需附加任何随机因素亦可出现类似随机的行为.在混沌的研究上,根据混沌系统提取的非线性时间序列对系统的未来进行预测,是一个十分重要的方面,混沌时间序列的非线性性给预测建模带来困难.关联向量机(RVM)是一种建立在支持向最机(SVW)之上的统计学习新方法.基于RVM埘以典型混沌时间序列为对象展开预测研究,实验表明在若干步内,RVM具有较高预测准确度,适用于混沌时间序列的多步预测.