Soft Sensor for Inputs and Parameters Using Nonlinear Singular State Observer in Chemical Processes

Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.

ASYMPTOTIC SOLUTION OF A SINGULARLY PERTURBED NONLINEAR STATE REGULATOR PROBLEM

This paper, will seek the optimal control and corresponding trajectories of the singularly perturbed nonlinear state regulator problem. Under appropriate hypotheses. it will be possible to complete an asymptotic solution which is uniformly valid when e→0.

Coherent States and a Path Integral for the Relativistic Linear Singular Oscillator

为线性单个振荡器的一个相对论的模型的协调状态被考虑的苏(1,1 ) 。相应分区功能被评估。为在协调状态被给的苏(1,1 ) 之间的转变振幅的路径积分。在概括弄弯的阶段空间的运动的古典方程被获得。这被显示出古典 Bohr Sommerfeld 量子化统治产出的伪的使用为精力光谱的准确表示。

The singularity in the state-based peridynamic solution of uniaxial tension

We solve the local uniaxial tension of an infinite rod in the framework of non-ordinary state-based peridynamics.The singular solutions of stress and displacement are acquired.When the influencing range of the window function approaches zero,these two solutions will return to the solutions of the classical elasticity.The analysis shows that the singularities of the solutions stem from such a feature of the window function that must be represented by a rapidly decreasing function in physics.Contrary to the classical elasticity,the stress solution of peridynamics is smoother than the displacement solution.In addition,a criterion used to select the window function is proposed in this paper.

奇异值分解五阶容积卡尔曼滤波汽车状态估计

针对三阶滤波对高维汽车非线性模型估计精度有限的问题,以电动汽车为研究对象,提出了一种基于奇异值分解的五阶容积卡尔曼滤波(SVD-FCKF)车辆状态估计器。首先基于Dugoff轮胎模型,构建高维非线性7自由度车辆动力学模型。然后根据三阶球面-径向容积规则将CKF拓展到五阶,使其具有五阶泰勒级数展开精度,同时利用奇异值分解代替传统Cholesky分解,提高估计器的鲁棒性。最后利用Carsim和Matlab/Simulink联合仿真平台对SVD-FCKF进行验证,结果表明:改进的SVD-FCKF估计器能够有效提高电动汽车纵向速度、侧向速度、质心侧偏角和四轮转速的估计精度和稳定性,多工况适应能力强,整体估计效果优于CKF估计器。研究结果为电动汽车主动安全研究提供了理论支撑,具有实际应用价值。

分布式驱动电动汽车状态与路面附着系数估计

【目的】准确获取车辆行驶状态参数和路面附着系数对于维持分布式驱动电动汽车的安全性和稳定性十分重要,针对于此,研究了一种能够准确估计其参数的算法,既能降低量产车辆的成本,又能达到车辆安全稳定的目的。【方法】首先,建立三自由度车辆模型,应用基于奇异值分解方法(SVD)的容积卡尔曼滤波算法搭建参数估计器。然后,搭建Carsim/Simulink联合仿真实验平台,采用高、低附着和对接路面双移线工况进行仿真验证。【结果】仿真实验结果表明,估计器能够较准确地估计出参数的真实值。基于仿真的良好估计效果,搭建实车实验平台,进一步进行验证得出,实车实验结果与仿真结果趋势一致,该算法具有较好的估计准确性和时效性。

基于自适应平方根容积卡尔曼滤波算法的分布式驱动车辆状态估计

为了解决分布式驱动电动汽车在实时车辆行驶状态难以获取、估计精度较低的问题,提出了基于奇异值分解(SVD)的平方根容积卡尔曼滤波(SCKF)的分布式驱动车辆状态估计方法。SCKF算法通过奇异值分解优化误差协方差矩阵,以改善CKF在强非线性车辆系统或协方差矩阵非正定时状态估计精度降低甚至发散的问题,利用7自由度车辆动力学模型和Dugoff轮胎模型求得的参数信息准确估计车辆行驶状态。在Matlab/Simulink仿真平台上进行试验验证,并与基于CarSim数据的虚拟值进行了对比分析。结果表明:基于该算法的估计结果更接近真实值,并且响应速度快、实时性强。

压力脉冲测试系统滑模抗干扰控制方法

针对压力脉冲测试系统运用滑模控制在体积切换时抖振突出的问题,提出一种滑模抗干扰控制方法。采用奇异值摄动理论对压力脉冲测试系统进行降阶简化,方便控制器的设计以及应用。根据系统降阶模型,构建扩张状态观测器,用于估计系统中的不确定参数和工件体积切换等未知干扰,并将估计的干扰值作为前馈信号补偿给滑模控制器,从而减小干扰不确定上界,减小切换增益来达到抑制抖振的目的。通过选择合适的Lyapunov函数对所提控制方法的稳定性进行了推导证明,使用AMESim、Matlab/Simulink构建的联合仿真平台进行仿真分析,并通过压力脉冲测试台进行了实验验证。研究结果表明:在整体跟踪性能方向,传统滑模控制方法相较于PID方法提升了21.10%,而所提控制方法相较于PID方法提升了30.86%,所提控制方法可以有效估计与补偿未知干扰,实现更小切换增益的同时保持控制精度,在工件体积切换时有效抑制了滑模抖振,提高了系统的抗干扰能力。

基于ESN模型的制造商库存需求预测

准确的库存需求预测对制造商提升库存管理能力具有重要意义。首先,针对制造商库存需求非平稳性、非线性和高波动的特点,使用奇异谱分析(SSA)和变分模态分解(VMD)实现特征工程,将原始数据分解为趋势信号和多种不同周期的信号,作为模型的输入。然后,引入回声状态网络(ESN),提出SSA-VMD-ESN模型,对库存需求进行预测。最后,将所提模型应用到Kaggle平台真实的制造商库存需求数据集中,与6种模型对比,并单独使用9个产品实验,结果表明所提出模型各项误差指标均属最优。由此证明,研究所提出模型可以有效提高库存需求预测的准确率,对库存管理具有较强的应用价值。

基于SVD-SUKF的水下机器人电池SOC估计

荷电状态(SOC)的准确估计关系到水下机器人的电池使用效率与任务规划。针对传统SOC估计算法存在的准确性、稳定性和鲁棒性不足等问题,提出一种奇异值分解增强的球型无迹卡尔曼滤波(SVD-SUKF)SOC估计算法。建立2阶Thevenin电路模型,并使用遗忘因子递推最小二乘法对模型参数进行在线辨识;在无迹卡尔曼滤波算法的基础上引入球型无迹变换和奇异值分解,避免繁琐的调参过程、减少算法计算量以及解决算法的协方差矩阵非正定问题;采用城市道路循环工况对SVD-SUKF算法进行验证。结果表明:SVD-SUKF算法收敛速度较快,平均绝对值误差为0.006 8、均方根误差为0.005 6,算法相较于扩展卡尔曼滤波和无迹卡尔曼滤波有更高的估计精度、更好的稳定性和更强的鲁棒性。

欺骗攻击下奇异跳变系统状态感知事件触发H_(∞)-脉冲混杂反馈控制

本文研究了在欺骗攻击下奇异马尔可夫跳变系统的状态感知事件触发H_(∞)-脉冲混杂反馈控制问题。为了进一步权衡控制性能和通信效率,提出了一种可根据当前系统状态自适应地调整事件触发阈值的基于周期采样的模态相关状态感知事件触发机制。基于所提出的事件触发机制,建立了一种模态相关的脉冲混杂反馈控制器。通过构造脉冲时间相关和马尔可夫跳变模态相关的Lyapunov-Krasovskii(L-K)泛函并结合奇异值分解技术,获得了奇异马尔可夫跳变系统在欺骗攻击下的H_(∞)随机容许性准则。在线性矩阵不等式框架下实现了状态感知事件触发器和H_(∞)-脉冲混杂反馈控制器协同设计。直流电机驱动负载的仿真实例验证了本文方法的有效性。

基于STESO的PMSM非奇异快速终端滑模控制

为了提高永磁同步电机驱动系统速度控制器的跟踪性能和鲁棒性,提出了一种基于超螺旋扩张状态观测器的非奇异快速终端滑模复合控制器。首先,采用一种基于新型变指数趋近律的非奇异快速终端滑模控制算法设计速度控制器,该趋近律在常规指数趋近律中引入系统状态变量,加快系统收敛到滑模面的速度,同时保持较小的抖振;其次,提出了一种超螺旋扩张状态观测器来观测系统的扰动,并补偿给速度控制器,提高了速度控制系统的鲁棒性;最后,通过仿真和实验证明所提方法的有效性。

Wave height estimation using the singular peaks in the sea echoes of high frequency radar

The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improve the accuracy and increase the valid detection range of the wave height measurement, particularly by the smallaperture radar, it is turned to singular peaks which often exceed the power of other frequency components. The power of three kinds of singular peaks, i.e., those around ±1,±√2 and ±1√2 times the Bragg frequency, are retrieved from a one-month-long radar data set collected by an ocean state monitoring and analyzing radar,model S（OSMAR-S）, and in situ buoy records are used to make some comparisons. The power response to a wave height is found to be described with a new model quite well, by which obvious improvement on the wave height estimation is achieved. With the buoy measurements as reference, a correlation coefficient is increased to 0.90 and a root mean square error（RMSE） is decreased to 0.35 m at the range of 7.5 km compared with the results by the second-order method. The further analysis of the fitting performance across range suggests that the peak has the best fit and maintains a good performance as far as 40 km. The correlation coefficient is 0.78 and the RMSE is 0.62 m at 40 km. These results show the effectiveness of the new empirical method, which opens a new way for the wave height estimation with the HF radar.

Observer-based robust predictive control of singular systems with time-delay and parameter uncertainties

The problem of observer-based robust predictive control is studied for the singular systems with norm-bounded uncertainties and time-delay, and the design method of robust predictive observer-based controller is proposed. By constructing the Lyapunov function with the error terms, the infinite time domain ＂min-max＂ optimization problems are converted into convex optimization problems solving by the linear matrix inequality （LMI）, and the sufficient conditions for the existence of this control are derived. It is proved that the robust stability of the closed-loop singular systems can be guaranteed by the initial feasible solutions of the optimization problems, and the regular and the impulse-free of the singular systems are also guaranteed. A simulation example illustrates the efficiency of this method.

THE DISTURBANCE LOCALIZATION PROBLEM FOR SINGULAR SYSTEMS

In this paper, we define the ({A,E},B)-invariant subspace pair contained in Ker C for singular systems, rigorously justifying the name and demonstrating the existence of the supremal ({A,E},B)-invariant;subspace pair contained in Ker C, we show how the supremal ({A,E},B)-invariant subspace pair contained in Ker C can be computed via some subspace recursions, We provide necessary and sufficient condition for the existence of a state feedback that achieves disturbance localization in a linear time-invariant singular system.

Singular linear quadratic performance with the worst disturbance rejection for descriptor systems

This paper deals with the problem of singular linear quadratic performance with the worst-disturbance rejection for descriptor systems. Under the conditions we give, the worst-disturbance and the optimal control-state pair are unique respectively, the optimal control can be synthesized as state feedback and the closed-loop system is regular, stable and impulse-free.

适用于次同步振荡分析的直驱风电场平衡降阶方法

直驱风电场(direct-drive wind farm,DDWF)并入弱交流系统存在发生次同步振荡(sub-synchronous oscillation,SSO)的风险。由于DDWF模型阶数较高,实际分析时须降阶处理。现有平衡降阶方法在分析SSO问题时,无法在降阶过程中精确保留系统SSO模式。针对此问题,文中提出一种适用于SSO分析的平衡降阶方法。该方法基于参与因子分析,保留与SSO模式强相关的状态变量,并结合Hankel奇异值确定降阶阶数,建立与全阶系统模型SSO特性和动态特性都一致的降阶系统模型。首先,对DDWF并入弱交流系统的全阶小信号模型进行平衡变换,建立平衡系统模型。然后,对平衡系统模型进行参与因子分析,结合Hankel奇异值确定保留状态变量集合,再利用残差降阶法建立降阶系统模型。最后,对全阶系统模型和降阶系统模型进行对比验证,结果表明所提降阶方法适用于DDWF并入弱交流系统SSO问题的研究。

Admissibility analysis and control synthesis for switched linear singular systems

The problem of admissibility analysis and control synthesis of discrete-time switched linear singular （SLS） systems for arbitrary switching laws is solved. By using the switched Lyapunov function approach, some new sufficient conditions under which the SLS system is admissible for arbitrary switching laws are derived in terms of linear matrix inequalities （LMIs）. Based on the admissibility results, control synthesis is then to design switched state feedback and static output feedback controllers, guaranteeing that the resulting closed-loop system is admissible. The presented results can be viewed as the extensions of previous works on switched Lyapunov function approach from the regular switched systems to singular switched cases. Examples are provided to demonstrate the reduced conservatism and effectiveness of the proposed conditions.

Robust Stabilization of Discrete-time Constrained Singular Piecewise-affine Systems with Norm-bounded Uncertainties

In this paper,the problem of designing robust H-infinity output feedback controller and l2-gain controller are investigated for a class of discrete-time singular piecewise-affine systems with input saturation and state constraints. Based on a singular piecewise Lyapunov function combined with S-procedure and some matrix inequality convexifying techniques,the H-infinity stabilization condition is established and the l2-gain controller is investigated,and meanwhile,the input saturation disturbance tolerance condition is proposed. Under energy bounded disturbance,the domain of attraction is well estimated and the l2-gain controller is designed in some restricted region. It is shown that the controller gains can be obtained by solving a family of LMIs parameterized by one or two scalar variables. Meanwhile,by using the corresponding optimization methods,the domain of attraction and the disturbance tolerance level is maximized,and the H-infinity performance γ is minimized.Finally,numerical examples are given to illustrate the effectiveness of the proposed design methods.