Some of the most common dynamic phenomena that arise in engineering practiceactuator and sensor delaysfall outside the scope of standard finite-dimensional system theory. The first attempt at ...infinite-dimensional feedback design in the field of control systemsthe Smith predictorhas remained limited to linear finite-dimensional plants over the last five decades. Shedding light on new opportunities in predictor feedback, this book significantly broadens the set of techniques available to a mathematician or engineer working on delay systems.The book is a collection of tools and techniques that make predictor feedback ideas applicable to nonlinear systems, systems modeled by PDEs, systems with highly uncertain or completely unknown input/output delays, and systems whose actuator or sensor dynamics are modeled by more general hyperbolic or parabolic PDEs, rather than by pure delay.Numerous examples and a detailed treatment of individual classes of problemswill help the reader master the techniques.Delay Compensation for Nonlinear, Adaptive, and PDE Systemsis an excellent reference guide for graduate students, researchers, and professionals in mathematics, systems control, as well as chemical, mechanical, electrical, computer, aerospace, and civil/structural engineering. Parts of the book maybe used in graduate courses on general distributed parameter systems, linear delay systems, PDEs, nonlinear control, state estimator and observers, adaptive control, robust control, or linear time-varying systems.
This article investigates the switching-like event-triggered control for networked control systems (NCSs) under the malicious denial of service (DoS) attacks. First, by dividing the DoS attacks into ...S-interval (DoS-free case) and D-interval (DoS case), a switching-like event-triggered communication scheme (SETC) is well designed to deal with intermittent DoS attacks to improve communication efficiency while keeping the desired control performance. Second, by considering the SETC and NCSs into a unified framework, the studied system is transferred into a time-delay system. Then, under the constraint of the number of maximum allowable data dropouts induced by DoS attacks, a stability criterion and a stabilization criterion are derived, which can be used to estimate the event-triggered communication parameters and obtain the security controller gain simultaneously. Moreover, the derived stabilization criterion can also provide a tradeoff to balance communication efficiency and <inline-formula><tex-math notation="LaTeX">H_{\infty }</tex-math></inline-formula> control performance. At last, a networked invert pendulum on a cart is conducted to show the effectiveness of the proposed method.
Military command and control is not merely evolving, it is co-evolving. Technology is creating new opportunities for different types of command and control, and new types of command and control are ...creating new aspirations for technology. The question is how to manage this process, how to achieve a jointly optimised blend of socio and technical and create the kind of agility and self-synchronisation that modern forms of command and control promise. The answer put forward in this book is to re-visit sociotechnical systems theory. In doing so, the problems of 21st century command and control can be approached from an alternative, multi-disciplinary and above all human-centred perspective.
We generalize and unify a range of recent results in quantized control systems (QCS) and networked control systems (NCS) literature and provide a unified framework for controller design for control ...systems with quantization and time scheduling via an emulation-like approach. A crucial step in our proofs is finding an appropriate Lyapunov function for the quantization/time-scheduling protocol which verifies its uniform global exponential stability (UGES). We construct Lyapunov functions for several representative protocols that are commonly found in the literature, as well as some new protocols not considered previously. Our approach is flexible and amenable to further extensions which are briefly discussed.
This paper considers the problem of practical stability for time‐varying positive systems with time delay. For both non‐linear time‐varying positive systems and linear time‐varying positive (LTVP) ...systems with time delay, sufficient conditions on practical stability are derived by the max‐separable Lyapunov‐Krasovskii (L–K) functional method. Then based on the obtained results, an effective method for designing a desired controller in terms of state feedback and state feedback with input delay is established for LTVP systems with time delay. At the end, numerical examples are presented to illustrate the effectiveness of our results.
This paper examines event-triggered data transmission in distributed networked control systems with packet loss and transmission delays. We propose a distributed event-triggering scheme, where a ...subsystem broadcasts its state information to its neighbors only when the subsystem's local state error exceeds a specified threshold. In this scheme, a subsystem is able to make broadcast decisions using its locally sampled data. It can also locally predict the maximal allowable number of successive data dropouts (MANSD) and the state-based deadlines for transmission delays. Moreover, the designer's selection of the local event for a subsystem only requires information on that individual subsystem. Our analysis applies to both linear and nonlinear subsystems. Designing local events for a nonlinear subsystem requires us to find a controller that ensures that subsystem to be input-to-state stable. For linear subsystems, the design problem becomes a linear matrix inequality feasibility problem. With the assumption that the number of each subsystem's successive data dropouts is less than its MANSD, we show that if the transmission delays are zero, the resulting system is finite-gain Lp stable. If the delays are bounded by given deadlines, the system is asymptotically stable. We also show that those state-based deadlines for transmission delays are always greater than a positive constant.
This paper provides a survey on modeling and theories of networked control systems ( NCS ). In the first part, modeling of the different types of imperfections that affect NCS is ...discussed. These imperfections are quantization errors, packet dropouts, variable sampling / transmission intervals, variable transmission delays, and communication constraints. Then follows in the second part a presentation of several theories that have been applied for controlling networked systems. These theories include: input delay system approach, Markovian system approach, switched system approach, stochastic system approach, impulsive system approach, and predictive control approach. In the last part, some advanced issues in NCS including decentralized and distributed NCS, cloud control system, and co-design of NCS are reviewed.
This note investigates the output feedback stabilization of networked control systems (NCSs). The sensor-to-controller (S-C) and controller-to-actuator (C-A) random network-induced delays are modeled ...as Markov chains. The focus is on the design of a two-mode-dependent controller that depends on not only the current S-C delay but also the most recent available C-A delay at the controller node. The resulting closed-loop system is transformed to a special discrete-time jump linear system. Then, the sufficient and necessary conditions for the stochastic stability are established. Further, the output feedback controller is designed via the iterative linear matrix inequality (LMI) approach. Simulation examples illustrate the effectiveness of the proposed method.
Industrial Control System (ICS) is a general term that includes supervisory control & data acquisition (SCADA) systems, distributed control systems (DCS), and other control system configurations such ...as programmable logic controllers (PLC). ICSs are often found in the industrial sectors and critical infrastructures, such as nuclear and thermal plants, water treatment facilities, power generation, heavy industries, and distribution systems. Though ICSs were kept isolated from the Internet for so long, significant achievable business benefits are driving a convergence between ICSs and the Internet as well as information technology (IT) environments, such as cloud computing. As a result, ICSs have been exposed to the attack vectors used in the majority of cyber-attacks. However, ICS devices are inherently much less secure against such advanced attack scenarios. A compromise to ICS can lead to enormous physical damage and danger to human lives. In this work, we have a close look at the shift of the ICS from stand-alone systems to cloud-based environments. Then we discuss the major works, from industry and academia towards the development of the secure ICSs, especially applicability of the machine learning techniques for the ICS cyber-security. The work may help to address the challenges of securing industrial processes, particularly while migrating them to the cloud environments.
In this work, we focus on model predictive control of nonlinear systems subject to data losses. The motivation for considering this problem is provided by wireless networked control systems and ...control of nonlinear systems under asynchronous measurement sampling. In order to regulate the state of the system towards an equilibrium point while minimizing a given performance index, we propose a Lyapunov-based model predictive controller which is designed taking data losses explicitly into account, both in the optimization problem formulation and in the controller implementation. The proposed controller allows for an explicit characterization of the stability region and guarantees that this region is an invariant set for the closed-loop system under data losses, if the maximum time in which the loop is open is shorter than a given constant that depends on the parameters of the system and the Lyapunov-based controller that is used to formulate the optimization problem. The theoretical results are demonstrated through a chemical process example.
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