There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Preface, Notations 1.Introduction to Time-Delay Systems I.Frequency-Domain Approach 2.Systems with Commensurate Delays 3.Systems withIncommensurate Delays 4.Robust Stability Analysis II.Time Domain Approach 5.Systems with Single Delay 6.Robust Stability Analysis 7.Systems with Multiple and Distributed Delays III.Input-Output Approach 8.Input-output stability A.Matrix Facts B.LMI and Quadratic Integral Inequalities Bibliography Index

/pdf/stability-of-time-delay-systems-5d2qjgdknf.pdf

Stability of Time-Delay Systems

There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

/pdf/a-survey-of-recent-results-in-networked-control-systems-2vqnhq8czm.pdf

A Survey of Recent Results in Networked Control Systems

1. Introduction. 2. Linear Algebra. 3. Linear Systems. 4. H2 and Ha Spaces. 5. Internal Stability. 6. Performance Specifications and Limitations. 7. Balanced Model Reduction. 8. Uncertainty and Robustness. 9. Linear Fractional Transformation. 10. m and m- Synthesis. 11. Controller Parameterization. 12. Algebraic Riccati Equations. 13. H2 Optimal Control. 14. Ha Control. 15. Controller Reduction. 16. Ha Loop Shaping. 17. Gap Metric and ...u- Gap Metric. 18. Miscellaneous Topics. Bibliography. Index.

/pdf/essentials-of-robust-control-3kaks6yk3h.pdf

Essentials of Robust Control

Orbital stations can be an alternative platform choice for SAR payloads besides professional remote sensing satellite platform. However, such platform cannot provide as precision motion parameters as remote sensing satellite platform for SAR imaging due to its unique structure. The influence of motion parameter errors on SAR azimuth resolution degradation should be taken into consideration. Selecting the second order phase error caused by Doppler frequency rate with error as intermediate variable between motion parameter errors and SAR azimuth resolution, this paper proposed a Monte Carlo simulation model has been set up to obtain the specific probability distribution of SAR azimuth resolution degradation. A typical Monte Carlo simulation result is given to show the effectiveness of the method and may help actual SAR payload system design.

Monte Carlo Analysis of Orbital Station Motion Parameter Errors Influence on Sar Azimuth Resolution Degradation

In highly-squint strip-map Synthetic Aperture Radar (SAR) onboard high-speed platform, the large range-walk is eliminated by continuously varying its pulse repetition interval (PRF), which overcomes the limitation of echo data collection. However, the accompanying problems of azimuth non-uniform sampling (ANS) and changing of Doppler history are inevitable. Therefore, an imaging formation algorithm for this SAR data imagery is proposed firstly. In the proposed algorithm, the range cell migration correction is performed to eliminate the changing of Doppler history. And the baseband Lagrange interpolation is implemented to reconstruct the ANS data. Then, the bulk compression function and stolt interpolation relationship are deduced in the focusing processing. Finally, the imaging results justify the validity and accuracy of the proposed algorithm.

Image formation algorithm for highly-squint strip-map SAR onboard high-speed platform using continuous PRF variation

Best tracking and regulation performance under control effort constraint: two-parameter controller case

To increase the global convergence and processing efficiency of particle swarm optimization (PSO) applied in the adaptive joint time-frequency, in this study an improved PSO is proposed to refocus the high-resolution SAR images of complex moving vessels in high sea states. According to the characteristics of the high-order multi-component polynomial phase signal, this algorithm provides parallel processing and co-evolution methods by setting the different permissions of the sub-population and sharing its search information. As a result, the multiple components can be extracted simultaneously. Experiments were conducted using the simulation data and Gaofen-3 (GF-3) SAR data. Results showed the processing speed increased by more than 40% and the global convergence was significantly improved. The imaging results verify the efficiency and robustness of this co-evolutionary PSO.

https://www.mdpi.com/2072-4292/12/20/3302/pdf

Refocusing High-Resolution SAR Images of Complex Moving Vessels Using Co-Evolutionary Particle Swarm Optimization

This paper reports a comprehensive study on an image processing and feature extraction tool particularly for 3-D range image applications in manufacturing processes. The library of the algorithms developed in this study is formatted into an easy-to-use imaging tool that consists of many useful algorithms and functions. The objective of this study is to produce a library of 3-D range imaging algorithms that can effectively employ imaging and vision techniques and be applied to industrial automation environments. A group of new algorithms have been developed and tested in manufacturing applications.

Jie Chen

Papers

Monte Carlo Analysis of Orbital Station Motion Parameter Errors Influence on Sar Azimuth Resolution Degradation

Image formation algorithm for highly-squint strip-map SAR onboard high-speed platform using continuous PRF variation

Best tracking and regulation performance under control effort constraint: two-parameter controller case

Refocusing High-Resolution SAR Images of Complex Moving Vessels Using Co-Evolutionary Particle Swarm Optimization

A 3-D robust range feature extraction tool for industrial automation applications