Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

Robust H_∞ Filter Design for 2D Discrete Systems in Roesser Model

This paper investigates the robust H ∞ filtering problem for uncertain two-dimensional (2D) systems described by the Roesser model. The parameter uncertainties considered in this paper are assumed to be of polytopic type. A new structured polynomially parameter-dependent method is utilized, which is based on homogeneous polynomially parameter-dependent matrices of arbitrary degree. The proposed method includes results in the quadratic framework and the linearly parameter-dependent framework as special cases for zeroth degree and first degree, respectively. A numerical example illustrates the feasibility and advantage of the proposed filter design methods.

Study on Robust H_∞ Filtering in Networked Environments

This paper is concerned with the robust H ∞ filter problem for networked environments, which are subject to both transmission delay and packet dropouts randomly. By employing random series which have Bernoulli distributions taking value of 0 or 1, the data transmission model is obtained. Based on state augmentation and stochastic theory, the sufficient condition for robust stability with H ∞ constraints is derived for the filtering error system. The robust filter is designed in terms of feasibility of one certain linear matrix inequality （LMI）, which is formed by adopting matrix congruence transformations. A numerical example is given to show the effectiveness of the proposed filtering method.

Robust H_∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.

基于ISSA-H_(∞)的水电机组鲁棒控制

随着风电、光伏等随机能源大量接入,电网结构变得复杂。在此背景下,水电机组将根据需要经常处于变工况运行,运行环境日趋恶劣,其传统的PID控制策略显然难以实现各种复杂工况下的最优控制。为此,将H_(∞)理论应用于水电机组,并基于改进樽海鞘算法(ISSA)和综合ITAE指标对其参数进行优化,实现了基于ISSA-H_(∞)的水电机组自适应鲁棒控制。仿真结果表明,相比传统的PID控制器,设计的基于ISSA-H_(∞)的自适应鲁棒控制器在不同工况下均有优异的调节性能,实现了水电机组多工况下最优控制。

具有扰动的不确定非线性多智能体系统的鲁棒H_(∞)二分一致性

研究了符号网络上具有参数不确定性和外部扰动的一类非线性时变多智能体系统(multi-agent system,MAS)的鲁棒H_(∞)二分一致性问题。采用鲁棒控制中处理不确定性的思想,将所考虑的系统转化为具有范数有界参数不确定性的时不变动力学模型。将鲁棒一致性转化为降阶H_(∞)控制问题。基于李雅普诺夫稳定性理论,得到了具有期望H_(∞)性能的多智能体系统鲁棒二分一致性的线性矩阵不等式(linear matrix inequality,LMI)充分条件。此外,给出了分布式静态输出反馈控制器的设计过程。进一步以二自由度(two-degree-of-freedom,2-DOF)的平面移动机器人为例,验证了所提出的控制器的有效性。

Robust H_∞ Filtering for a Class of Uncertain Lurie Time-delay Singular Systems

这份报纸处理与州的时间延期，参数无常和未知统计特征，但是与有限力量骚乱为 Lurie 单个系统的一个班过滤的柔韧的 H 的问题，试图设计一个要用体力地稳定的过滤器以便单个系统是的不明确的 Lurie 时间延期不仅常规，免费、稳定的推动，而且为所有可被考虑的无常为过滤错误动力学有 H 性能的规定水平。为如此的一个过滤器的存在的一个足够的条件以线性矩阵不平等(LMI ) 被建议。当 LMI 的这个集合的一个答案存在时，一个需要的过滤器的参量的矩阵能容易用 LMI 工具箱被获得。

基于平方根容积卡尔曼滤波的核反应堆功率H_(∞)控制

核反应堆的负荷跟踪控制是核电站灵活调峰、具有应用价值的基础之一.根据反应堆中子动力学、热工水力、反应性方程等数学模型构建了反应堆的平方根容积卡尔曼滤波器(Square-root Cubature Kalman Filter,SCKF),对反应堆状态反馈问题中部分状态量无法量测或估计精度不足的问题加以解决,结合离散H_(∞)性能指标设计了基于SCKF的反应堆功率H_(∞)控制器,并与基于经典卡尔曼滤波器(Kalman Filter,KF)的反应堆功率H_(∞)控制器进行了同工况数值仿真对比.仿真结果表明,基于SCKF的功率控制器具有较好的负荷跟踪性能,能够根据期望跟踪目标调节反应堆功率水平;由于SCKF对非线性系统模型相比于KF具有更高的状态估计精度,基于SCKF的功率控制器相比基于KF的功率控制器具有更优的控制效果.

A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

Design of H_∞ robust fault detection filter for nonlinear time-delay systems

In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. First, a reference residual model is introduced to formulate the RFDF design problem as an H∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the RFDF for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.

基于变分贝叶斯的容积H_(∞)滤波在无人船载低成本MIMU对准的应用

无人船在恶劣海况下对其船载低成本微机械惯性测量单元(micro inertial measurement unit,MIMU)进行初始对准,其精度不仅会受到海浪摇摆、浪涌等未知复杂干扰的影响,还会受传感器噪声的影响。针对这一问题,提出基于变分贝叶斯的H_(∞)滤波算法(variational Bayesian cubature H_(∞)filter,VBCH),从而实现在系统噪声或状态方程不确定且系统噪声和量测噪声同时具有“时变”“厚尾”特性情况下的自适应鲁棒滤波。仿真实验表明,随着MIMU噪声的增大以及各项误差系数的不稳定性增强,系统噪声和状态方程逐渐变得不确定,基于卡尔曼滤波的自适应算法逐渐失效,而本文提出基于H_(∞)控制理论VBCH算法则能够继续保持一定的对准精度和算法鲁棒性:对无人船载低精度MIMU的天向对准精度达到1.5°,东向、北向对准精度能达到0.1°。满足无人船大失准角初始对准的要求,具有一定的应用价值。

Robust H_∞ filtering for discrete-time impulsive systems with uncertainty

This paper investigates robust filter design for linear discrete-time impulsive systems with uncertainty under H∞ performance. First, an impulsive linear filter and a robust H∞ filtering problem are introduced for a discrete-time impulsive systems. Then, a sufficient condition of asymptotical stability and H∞ performance for the filtering error systems are provided by the discrete-time Lyapunov function method. The filter gains can be obtained by solving a set of linear matrix inequalities （LMIs）. Finally, a numerical example is presented to show effectiveness of the obtained result.

Krein space approach to robust H_∞ filtering for linear uncertain systems

A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint （SQC） without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.

Robust H_∞ Filter Design for a Class of Uncertain Linear Systems with Time-delayed Measurement

A robust H∞ approach to filtering for a class of uncertain linear systems with time-delayed measurement is investigated. The parameter uncertainties are described by real time-varying norm-bounded form. A methodology is developed for designing linear filters such that the filtering process remains robustly stable and the transfer function from the disturbance inputs to error state outputs meets the prescribed H∞-norm upper-bound constraints. The filter can be obtained and parameterized by solving two Riccati equations based on the lemma of robust stability for control system with delay. Simulation example proves the method to be effective and feasible.

Robust H_∞ filtering for neutral jump system with time-delays and uncertainties

The problem of robust H∞ filtering for a class of neutral jump systems with time-delay and norm-bounded uncertainties is considered. By re-constructing the system, the dynamics of overall augmented error systems is obtained which involves unknown inputs represented by disturbances, model uncertainties and time-delays. As to the nominal system, sufficient conditions are provided for the existence of the mode-dependent H∞ filter by selecting the appropriate Lyapunov-Krasovskii function and the robust H∞ filter is proposed for the jump system while considering the time-delays and uncertainties. Both of above conditions for the existence of the H∞ filter and roust H∞ filter are presented in terms of linear matrix inequalities, and convex optimization problems are formulated to design the desired filters. By employing the proposed mode-dependent H∞ filter, the systems have the stochastic stability and better ability of restraining disturbances stochastically, and the given prescribed H∞ performance is guaranteed. Simulation results illustrate the effectiveness of developed techniques.

电站锅炉-汽轮机系统的LPV鲁棒H_(∞)/H_(2)变增益控制

采用量子粒子群算法辨识得到机炉协调控制系统的全局线性参数变化(LPV)模型,然后通过极值分解组合得到多胞LPV模型。针对多胞LPV模型,在鲁棒H_(∞)/H_(2)变增益控制中引入松弛变量,设计了保守性更低的机炉协调控制系统鲁棒控制器。结果表明:所设计的控制器具有良好的控制效果。

基于自适应H_(2)/H_(∞)滤波的锂电池SOC和SOH联合估计

准确、实时地估计电池的荷电状态(state of charge,SOC)和健康状态(state of health,SOH)是现代电池管理系统的关键任务。通过自适应H_(2)/H_(∞)滤波器可对锂电池的SOC和SOH进行联合估计。该方法基于锂电池的二阶RC等效电路模型,采用AFFRLS法在线辨识锂电池的模型参数,并利用H_(2)/H_(∞)滤波器估计锂电池的SOC,AFFRLS辨识与H_(2)/H_(∞)滤波交替进行,得到一种自适应H_(2)/H_(∞)滤波器。SOH依据AFFRLS辨识的电池内阻进行估计,实现了锂电池SOC与SOH的联合估计。实验结果表明:自适应H_(2)/H_(∞)滤波算法的估计精度高且鲁棒性强,电池的SOC和SOH的平均估计误差始终保持在±0.19%以内,相比于EKF和H_(∞)滤波算法有更高的估计精度与稳定性。

数值界不确定直流微电网的鲁棒H_(∞)控制

针对直流微电网中参数不确定问题,提出了基于LMI的鲁棒H_(∞)控制方法,以保证系统直流母线电压稳定.首先,建立直流微电网的范数有界不确定小信号模型.其次,根据Lyapunov稳定性原理,推导了基于LMI的控制器存在的充分条件,把鲁棒H_(∞)控制器的设计转化为具有线性矩阵不等式的优化问题,进而求出状态反馈控制律,使得每个子系统和关联大系统都可镇定,且鲁棒H_(∞)控制器存在可行解.最后,通过Matlab进行数值仿真,分析了微电网结构变化、连接线路参数和负载参数变化情况下直流母线电压的特性,验证了该控制方法的可行性.

量化误差下具有多丢包的信息物理系统H_(∞)滤波

研究一类具有信息传输不完全的信息物理系统H_(∞)滤波问题,考虑的信息传输不完全现象主要包括通信设备缺陷引起的量化误差和网络固有因素造成的连续随机多数据包丢失。采用Delta算子离散化方法构建信息物理系统状态空间模型和H_(∞)滤波器模型,通过分析和建模将量化误差和丢包模型与滤波器模型结合得出滤波误差系统。利用Lyapunov稳定性理论和Schur补引理推导出保证系统渐近稳定和H_(∞)性能的2个定理。基于目标追踪系统进行滤波器的仿真验证,结果表明:当量化器的参数固定时,随着最大丢包数的增加,H_(∞)性能指标γ逐渐增大,即数据包丢失越严重对系统稳定性造成的影响越大,但所设计的滤波器仍满足稳定性条件。所提滤波方法是有效的。

无记忆状态反馈广义H_(2)控制

对系统存在无记忆状态广义控制器进行了理论深化,讨论了时滞依赖和时滞独立2种情形下,无记忆状态广义H_(2)控制器存在的充分性判别条件和具体设计方法.设计了一个无记忆状态广义H_(2)控制器,采用新的引理,推出了保守性相对更小的稳定性判据.对所得结论进行了线性化处理,用数值样例验证了本文所得结论的有效性和可行性.指出在零到奇异摄动上界的整个区间范围内,闭环系统渐近稳定,扩大了广义H_(2)稳定空间,缩小了L_(2)-L_(∞)性能指标.通过与相关文献进行稳定态指标对比,本文所得方法具有一定的优越性和较小的保守性,并且适用于标准和非标准情形.