[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system. Limitations on results are carefully detailed and the case of oscillator noise is considered. The theory is extended to multiple input-multiple output systems.

Linear System Theory

Neural networks

A recent set of overused population-based methods have been published in recent years. Despite their popularity, most of them have uncertain, immature performance, partially done verifications, similar overused metaphors, similar immature exploration and exploitation components and operations, and an insecure tradeoff between exploration and exploitation trends in most of the new real-world cases. Therefore, all users need to extensively modify and adjust their operations based on main evolutionary methods to reach faster convergence, more stable balance, and high-quality results. To move the optimization community one step ahead toward more focus on performance rather than change of metaphor, a general-purpose population-based optimization technique called Hunger Games Search (HGS) is proposed in this research with a simple structure, special stability features and very competitive performance to realize the solutions of both constrained and unconstrained problems more effectively. The proposed HGS is designed according to the hunger-driven activities and behavioural choice of animals. This dynamic, fitness-wise search method follows a simple concept of “Hunger” as the most crucial homeostatic motivation and reason for behaviours, decisions, and actions in the life of all animals to make the process of optimization more understandable and consistent for new users and decision-makers. The Hunger Games Search incorporates the concept of hunger into the feature process; in other words, an adaptive weight based on the concept of hunger is designed and employed to simulate the effect of hunger on each search step. It follows the computationally logical rules (games) utilized by almost all animals and these rival activities and games are often adaptive evolutionary by securing higher chances of survival and food acquisition. This method's main feature is its dynamic nature, simple structure, and high performance in terms of convergence and acceptable quality of solutions, proving to be more efficient than the current optimization methods. The effectiveness of HGS was verified by comparing HGS with a comprehensive set of popular and advanced algorithms on 23 well-known optimization functions and the IEEE CEC 2014 benchmark test suite. Also, the HGS was applied to several engineering problems to demonstrate its applicability. The results validate the effectiveness of the proposed optimizer compared to popular essential optimizers, several advanced variants of the existing methods, and several CEC winners and powerful differential evolution (DE)-based methods abbreviated as LSHADE, SPS_L_SHADE_EIG, LSHADE_cnEpSi, SHADE, SADE, MPEDE, and JDE methods in handling many single-objective problems. We designed this open-source population-based method to be a standard tool for optimization in different areas of artificial intelligence and machine learning with several new exploratory and exploitative features, high performance, and high optimization capacity. The method is very flexible and scalable to be extended to fit more form of optimization cases in both structural aspects and application sides. This paper's source codes, supplementary files, Latex and office source files, sources of plots, a brief version and pseudocode, and an open-source software toolkit for solving optimization problems with Hunger Games Search and online web service for any question, feedback, suggestion, and idea on HGS algorithm will be available to the public at https://aliasgharheidari.com/HGS.html .

Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts

<p style='text-indent:20px;'>This paper focuses on the problem of fault detection filtering (FDF) for continuous-time singular systems via a dynamic event-triggered mechanism. Firstly, in order to reduce signal transmission and save network resources, a dynamic event-triggered mechanism is adopted. Compared with the static mechanism, the proposed method is more effective on reducing network transmission pressure since a dynamic variable is introduced. Secondly, a novel criterion is derived to guarantee the admissibility of the residual system with a certain <inline-formula><tex-math id="M1">\begin{document}$ \mathcal{H}_\infty $\end{document}</tex-math></inline-formula> performance. According to the derived conditions, a new method is given to codesign the desired filter and the event-triggered parameters. Finally, an example is employed to illustrate the validity of the proposed approach.</p>

Fault detection filtering for continuous-time singular systems under a dynamic event-triggered mechanism

This study focuses on the secure stability issue of networked control systems (NCSs) under injection cyber-attacks (ICAs), which have important research value of applications for network security. Firstly, a more general Lyapunov–Krasovskii functional (LKF) is constructed based on the time-delay phenomenon in systems. Secondly, a novel boundary looped function (BLF) is developed depending on the sampling period, fully considering delay and sampling information, and the initial constraints of the criteria on the matrices are effectively relaxed. In addition, appropriate integral inequalities are used, making the obtained criteria less conservative in this paper. Then, a new event-trigger mechanism (ETM) controller under ICAs is designed to control the asymptotical stability (AS) of NCSs. Finally, a numerical experiment verifies the correctness and feasibility of the theory.

/pdf/secure-event-triggered-mechanism-for-networked-control-8h35l2ue.pdf

Secure Event-Triggered Mechanism for Networked Control Systems under Injection Cyber-Attacks

For time-delay systems, a new refined Lyapunov function is proposed, whose derivative is not estimated by the integral inequalities, but is directly applied to linear matrix inequality conditions after using the existing study and then combines the derivative function with Lemma 1. Meantime, some useful cross terms appear to be good for lower conservatism. The numerical results show that such simple functional form would reduce the conservativeness of conditions slickly.

A New Refined Lyapunov Functional for Time-Varying Delayed Systems

In this article, observed-based discrete proportion-integration-differentiation (PID) control for multi-area interconnected power systems is addressed under hybrid attacks. Firstly, a reconstructed jump model for interconnected power systems is proposed by taking the circumstance of data packet loss into consideration, which caused by the stochastic transmission delay of sampled data. Then, different from the traditional continuous-type PID control, an observer-based discrete-type PID control strategy is designed for discrete-time power system. Besides, due to the sampled data may be tampered or shield in open communication networks, the hybrid attacks, i.e., deception attacks and denial-of-service attacks, with random manners are considered. Furthermore, an input-to-state stable criterion is derived by constructing appropriate Lyapunov-Krasovskii functionals. Finally, the discrete-type PID controllers and observer are achieved, and the validity of proposed approach are also demonstrated in the illustrative examples section.

Kaibo Shi

Papers

Fault detection filtering for continuous-time singular systems under a dynamic event-triggered mechanism

Secure Event-Triggered Mechanism for Networked Control Systems under Injection Cyber-Attacks

A New Refined Lyapunov Functional for Time-Varying Delayed Systems

Design of Observer-Based Discrete-Type PID Control for Reconstructed Jump Model of Interconnected Power System Under Hybrid Attacks

Distributed secure sampled-data control for distributed generators and energy storage systems in microgrids under abnormal deception attacks