Control Systems

Control systems play a vital role in the advancement of many engineering and science fields. The increasing demand for safety and reliability has led to the development of fault diagnosis (FD) and fault-tolerant control (FTC) systems, which play a paramount role in safety-critical systems, such as water distribution networks, aircrafts, spacecrafts, chemical, and biochemical plants, and nuclear power plants, where even minor faults can lead to catastrophic consequences. FD has primary importance since it enables online monitoring processes, allowing for the implementation of so-called active FTC systems. In an active FTC system, the FD module determines which component exhibits abnormal behavior and feeds this information to the controller. Based on this information, it redistributes or adapts the control law to maintain stability with a controlled degradation of the system's performance. Therefore, there is an increasing interest in creating new techniques or adapting the existing fault diagnosis and fault-tolerant methods to make the above-mentioned systems secure. At the same time, control theory is developing ceaselessly, and new theoretical results are continually being discovered that can be used in innovative fault diagnosis and fault-tolerant control techniques.

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis.

Although framework technology has proven its worth as a software reuse technique in many domains, there have been reservations regarding its application in embedded systems, mostly due to limited CPU and memory resources. Recent hardware advances, however, have changed this picture.

In the rapidly evolving landscape of nonlinear control systems, this reprint stands as a beacon of knowledge, showcasing the remarkable progress made over the last few decades. With a focus on design methodologies and their applications, this text employs various mathematical tools to address the myriad challenges inherent in nonlinearly controlled systems. This reprint extends its reach beyond traditional boundaries, presenting applications of nonlinear control across diverse fields such as energy, health care, robotics, biology, and big data research. As technology continues to advance, nonlinear control emerges as a critical player in shaping the future of theory and technology adoption across these domains. Despite the wealth of the existing literature, synthesizing control strategies for a broader class of nonlinear systems, especially those integrated with emerging technologies in communication and computation, remains a formidable task.

Changsheng Hua proposes two approaches, an input/output recovery approach and a performance index-based approach for robustness and performance optimization of feedback control systems. For their data-driven implementation in deterministic and stochastic systems, the author develops Q-learning and natural actor-critic (NAC) methods, respectively. Their effectiveness has been demonstrated by an experimental study on a brushless direct current motor test rig.

One service mathematics has rendered the 'Bt mm, …· si j'avait su comment en revenir, human race. It has put common sense back je n'y serais point alIe.' Jules Verne where it belongs. on the topmost shelf next to the dusty canister labelled 'discarded non­ The series is divergent; therefore we may be sense'. Eric T. Bell able to do something with it.

This book provides profound insights into industrial control system resilience, exploring fundamental and advanced topics and including practical examples and scenarios to support the theoretical approaches. It examines issues related to the safe operation of control systems, risk analysis and assessment, use of attack graphs to evaluate the resiliency of control systems, preventive maintenance, and malware detection and analysis. The book also discusses sensor networks and Internet of Things devices.