Robust and optimal control of AC machines

Fault-tolerant cooperative control of multiagent systems has attracted ever-increasing attention in recent years due to the fact that multiple agents can provide much more redundancy than a single agent system, thereby making the fault tolerant cooperative control design more flexible. However, multiagent systems may bring severe challenges that do not exist in single-agent systems. This article aims at presenting a survey of trends and methodologies of fault tolerant cooperative control in multiagent systems. Depending on the countermeasure against the faults, the existing fault-tolerant cooperative control methodologies are first classified into four categories: Individual methodologies, cooperative methodologies, topology reconfiguration-based methodologies, and composition reconfiguration-based methodologies. Then the characteristics and implementation schemes of four categories of methodologies are discussed in detail. Furthermore, the applicability of fault tolerant cooperative control in smart grids is outlined. Finally, several challenging issues are envisioned for future research.

Fault-Tolerant Cooperative Control of Multiagent Systems: A Survey of Trends and Methodologies

A novel classiflcation framework is proposed, which divides fault diagnosis approaches into two classes: qual- itative analysis approaches and quantitative analysis approaches The basic idea, main research progresses, and typical applications of each method are discussed in detail, with emphasis on the data-driven approaches The state-of-the-art of fault prediction is also outlined Finally, some problems and development trends of the research on fault diagnosis are pointed out

Fault Diagnosis Techniques for Dynamic Systems

https://personalpages.manchester.ac.uk/staff/jian-bo.yang/JB%20Yang%20Journal_Papers/ZhouWuXuYangZhou_IS_Predict_Behaviour.pdf

New model for system behavior prediction based on belief rule based systems

Summary

In this paper, we consider the recursive state estimation problem for a class of discrete-time nonlinear systems with event-triggered data transmission, norm-bounded uncertainties, and multiple missing measurements. The phenomenon of event-triggered communication mechanism occurs only when the specified event-triggering condition is violated, which leads to a reduction in the number of excessive signal transmissions in a network. A sequence of independent Bernoulli random variables is employed to model the multiple measurements missing in the transmission. The norm-bounded uncertainties that could be considered as external disturbances which lie in a bounded set. The purpose of the addressed filtering problem is to obtain an optimal robust recursive filter in the minimum-variance sense such that with the simultaneous presence of event-triggered data transmission, norm-bounded uncertainties, and multiple missing measurements; the filtering error is minimized at each sampling time. By solving two Riccati-like difference equations, the filter gain is calculated recursively. Based on the stochastic analysis theory, it is proved that the estimation error is bounded under certain conditions. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed algorithm. Copyright © 2016 John Wiley & Sons, Ltd.

Recursive state estimation for discrete‐time nonlinear systems with event‐triggered data transmission, norm‐bounded uncertainties and multiple missing measurements

A survey on fault prediction techniques in dynamic systems was presented. Firstly, the importance of these techniques was introduced. Then the available fault prediction techniques were classified into three categories, and the advantages and disadvantages of those techniques were discussed. Moreover, several typical examples were presented to show the effectiveness of the techniques. Finally, further problems to be addressed and trends in this field were tentatively pointed out.

Fault prediction techniques for dynamic systems

Remaining useful life prediction for a nonlinear multi-degradation system with public noise

Image registration plays an important role in terrain-aided navigation system.Normalized cross correlation method(NCC)is a relatively good method with anti-noise ability and precise.It is widely used in the navigation system.Because the computing quantity is huge,it needs to be improved in order to satisfy the fastness of navigation.A method based on NCC and convolution is proposed.It becomes much more fast.Experimental results verify its efficiency and fastness.

Zhou Dong-hua

Papers

Fault prediction techniques for dynamic systems

Remaining useful life prediction for a nonlinear multi-degradation system with public noise

Fast matching method based on NCC

Fault Detection and Diagnosis for a Class of Nonlinear Systems with Decentralized Event-triggered Transmissions

Fault Diagnosis of the Planetary Gearbox Based on ssDAG-SVM