Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

Passivity-based non-fragile control for Markovian jump delayed systems via stochastic sampling

This paper studies the problem of non-fragile passive control for Markovian jump delayed systems via stochastic sampling. The Markovian jumping parameters, appearing in the connection weight matrices and in two additive time-varying delay components, are considered to be different. The controller is assumed to have either additive or multiplicative norm-bounded uncertainties. The sampled-data with stochastic sampling is used to design the controller by a discontinuous Lyapunov functional. This functional fully utilises the sawtooth structure characteristics of the sampling input delay. By using the matrix decomposition method and some newly inequalities, sufficient conditions are obtained to guarantee that for all admissible uncertainties the system is robustly stochastically passive. Illustrative examples are provided to show the effectiveness of the results.     

Controlling aliased dynamics in motion systems? An identification for sampled-data control approach

Sampled-data control systems occasionally exhibit aliased resonance phenomena within the control bandwidth. The aim of this paper is to investigate the aspect of these aliased dynamics with application to a high performance industrial nano-positioning machine. This necessitates a full sampled-data control design approach, since these aliased dynamics endanger both the at-sample performance and the intersample behaviour. The proposed framework comprises both system identification and sampled-data control. In particular, the sampled-data control objective necessitates models that encompass the intersample behaviour, i.e., ideally continuous time models. Application of the proposed approach on an industrial wafer stage system provides a thorough insight and new control design guidelines for controlling aliased dynamics.     

On the Development of Analogue Sampled-Data Signal Processing

This paper provides a historical perspective on thedevelopment of analogue sampled-data signal processing circuitsand systems. The evolution, role and current trends in the developmentof analogue sampled-data signal processing systems is surveyed.Firstly, the evolution of integrated circuit based techniques,culminating in the ubiquitous switched-capacitor technique istraced. Then the role that analogue sampled-data systems playwithin the context of a general information processing environmentis examined and the required characteristics are identified.Trends in silicon integrated circuit processing technology aresummarised and their impact on sampled analogue circuits areidentified. Finally, the application of analogue current-modetechniques, and in particular switched-currents, to overcomesome of the limitations of previous voltage based approaches,is discussed.     

State Estimation for Non-linear Sampled-Data Descriptor Systems: A Robust Extended Kalman Filtering Approach

非线性广义采样系统的状态估计—鲁棒扩展卡尔曼滤波方法

王茂¹,梁天添¹,周振华²

(1.哈尔滨工业大学 空间控制与惯性技术研究中心,哈尔滨 150001;

2.常州工业职业技术学院,江苏 常州 213000)

创新点说明：

1）引入参数并使用欧拉离散化方法将广义连续-离散系统转化为非奇异一般系统进行研究;

2）针对转化得来的非奇异系统中存在状态新增不确定性的问题,提出鲁棒上界,并根据该上界设计鲁棒扩展卡尔曼滤波器（REKF）;

3）对设计的滤波器鲁棒性进行证明,证明该滤波器符合鲁棒性能指标。

研究目的、方法：

为解决一类范数有界非线性广义连续-离散系统的状态估计问题,在Matlab环境下,对REKF与EKF算法进行仿真对比

研究结果：

仿真结果表明,由REKF算法得到的状态估计误差小于EKF算法得到结果的20%,相较于EKF算法,REKF算法能更好估计该类广义系统的状态。

结论：

1）提出的REKF算法可有效解决系统非线性问题;

2）提出的鲁棒算法可有效降低非奇异等价系统中新增状态不确定性对状态估计影响;

3）相较于EKF算法,本文提出的REKF算法能够保证状态估计误差协方差矩阵有效收敛,从而能更好的估计该类广义连续-离散系统的状态。

关键词：采样系统;广义系统;状态估计;卡尔曼滤波;REKF算法

     

Absolute stability of sampled-data systems with a sector nonlinearity

This paper studies the absolute stability problem of sampled-data systems with a sector nonlinearity. Using the FR-operator technique, a frequency-domain criterion with a Nyquist-like plot is derived. It can be regarded as a sampled-data version of the circle criterion. It is shown that the “absolute-stability gain margin” can be read directly from the plot.     

Fault-tolerant control for a class of nonlinear sampled-data systems via a Euler approximate observer

In this paper, a fault-tolerant control (FTC) scheme is developed for a class of nonlinear sampled-data systems. First, a Euler approximate discrete model is used to describe the plant under the sampling. Under this model, an observer-based fault estimation method is proposed. To guarantee the accuracy of both the state and fault estimation values, the conditions to make the approximate model consistent with the exact model are presented. Then, an active fault-tolerant controller, which has a constraint condition for the sampling time, is designed to make the faulty system stable. Finally, an inverted pendulum is used to show the efficiency of the proposed method.     

采样数据系统故障检测的H∞方法

提出一种对采样数据系统进行故障检测的H_∞方法. 首先构造离散时间故障检测系统, 分析残差产生器的动态特性. 然后从故障检测的角度引入算子, 定量考察连续时间未知输入信号和故障信号对离散时间残差信号的影响. 最后优化残差产生器的参数, 使得故障检测系统对未知输入具有较强的鲁棒性, 同时对故障具有较高的灵敏度.     

H∞离散化的MATLAB程序

提升技术现已成为采样控制系统分析和设计的主要工具。系统提升后成为一离散系统，其H∞范数与原采样系统的L2诱导范数是等价的，故称为H∞离散化。提升计算包括矩阵的指数和积分运算，一般是很复杂的。本文给出了利用MATLAB的提升算法，算法简单可靠；同时还给出了求取等价系统H∞范数γ值的二分法并配有算例。     

线性切换系统的采样数据输出调节问题

本文基于采样控制,解决了线性切换系统的输出调节问题.首先考虑了外部输入信号是常数的情况,给出了采样周期与平均驻留时间的关系.通过构造一类Lyapunov-Krasovskii泛函,使得闭环系统内部稳定且调节输出趋于零.其次考虑了外部输入信号是导数有界且时变的情况,给出了采样数据状态反馈控制器,并依据采样周期和平均驻留时间关系给出的切换条件得到了切换系统实用输出调节问题可解的充分条件.最后通过两个数值例子验证了方法的有效性.