基于无记忆降阶观测器的网络化控制系统故障检测方法

网络化控制系统(Networked Control System,简称NCS)研究的是如何通过网络实现闭 环控制,是涉及控制科学和计算机网络等多个学科知识的跨学科研究领域.本文将网络化控制系 统视为带有时延的采样控制系统,构造了一个无记忆的降阶状态观测器,通过比较观测器输出和 系统实际输出来产生残差,从而对网络化系统的控制故障进行了检测.仿真结果表明此方法是可 行的.  

保代价采样控制在打浆过程中的应用

针对打浆过程计算机控制系统提出了保代价采样控制，当系统存在结构不确定时，该方法能使系统闭环鲁棒稳定，且系统的性能指标达到一定的要求，理论分析和仿真结果表明，保代价采样控制是打浆过程一种有效可行的控制方案。  

A bound of conservativeness in sampled-data robust stabilization and its dependence on sampling periods

This paper investigates conservativeness of the ²-induced norm in a sampled-data robust stabilization problem. Namely, it is shown that possible conservativeness of the ²-induced norm can be bounded by difference between the best achievable performance of time-invariant continuous-time controllers and that of sampled-data controllers. Moreover, this difference is proven to approach zero as a sampling period tends to zero, which means the conservativeness above loses importance when a sampling period is small. These results are important because robust stabilization based on the ²-induced norm is computationally inexpensive compared with robust stabilization based on the non-conservative robust stability index. One key lemma plays an essential role in this paper and it should be interesting independently.  

A refined input delay approach to sampled-data control

This paper considers sampled-data control of linear systems under uncertain sampling with the known upper bound on the sampling intervals. Recently a discontinuous Lyapunov function method was introduced by using impulsive system representation of the sampled-data systems (Naghshtabrizi, Hespanha, & Teel, 2008). The latter method improved the existing results, based on the input delay approach via time-independent Lyapunov functionals. The present paper introduces novel time-dependent Lyapunov functionals in the framework of the input delay approach, which essentially improve the existing results. These Lyapunov functionals do not grow after the sampling times. For the first time, for systems with time-varying delays, the introduced Lyapunov functionals can guarantee the stability under the sampling which may be greater than the analytical upper bound on the constant delay that preserves the stability. We show also that the term of the Lyapunov function, which was introduced in the above mentioned reference for the analysis of systems with constant sampling, is applicable to systems with variable sampling.  

采样系统的提升法H∞设计:条件和局限性

The initial motivation of the lifting technique is to solve the H∞ control problems.However, the conventional weighted H∞ design does not meet the conditions required by lifting, so the result often leads to a misjudgement of the design. Two conditions required by using the lifting technique are presented based on the basic formulae of the lifting. It is pointed out that only the H∞ disturbance attenuation problem with no weighting functions can meet these conditions, hence,the application of the lifting technique is quite limited.  

Stability and stabilization of nonuniform sampling systems

This paper is concerned with nonuniform sampling systems, where the sampling interval is time-varying within a certain known bound. The system is transformed into a time-varying discrete time system, where time-varying parts due to the sampling interval variation are treated as norm bounded uncertainties using robust control techniques. To reduce conservatism arising from modeling time-varying parts as a single uncertainty, the time-varying parts are modeled as N uncertainties. With larger N, a less conservative stability condition is derived at sacrifice of more computation. It is shown through a numerical example that the proposed stability condition is better than existing stability conditions.  

Output dead-beat control for nonlinear systems with one zero at infinity

The problem of output dead-beat control, i.e. one-step zeroing of the output, is considered for nonlinear systems with discrete-time controllers. The nonlinear system is assumed to have one zero at infinity. Conditions for the existence of the dead-beat control for small sampling intervals are derived. The closed-loop system is shown to be stable in the sense that all states converge to the origin if the controlled system is minimum phase.  

Nonlinear sampled-data output feedback receding horizon control

In this paper, we present an output feedback receding horizon control for a class of SISO nonlinear systems. A globally stabilizing state feedback receding horizon control scheme is combined with a discretized high gain observer. This is motivated by the fact that measurable system’s outputs are only available at specific sampling intervals. Our result follows from the application of a separation principle applicable to a class of sampled-data nonlinear systems. It is shown that the output-feedback scheme recovers the performance (rate of convergence) achieved under state feedback receding horizon control for a sufficiently large observer gain and sampling frequency.