Stealthy Measurement-Aided Pole-Dynamics Attacks With Nominal Models.

When traditional pole-dynamics attacks (TPDAs) are implemented with nominal models, model mismatch between exact and nominal models often affects their stealthiness, or even makes the stealthiness lost. To solve this problem, this article presents a novel stealthy measurement-aided pole-dynamics attacks (MAPDAs) method with model mismatch. First, the limitations of TPDAs using exact models are revealed.

A Novel Scalable and Reliable Control for DC Microgrids With Varying Number of Agents.

Existing scalable control methods mainly rely on a fixed block-diagonal structure for the Lyapunov matrix, potentially resulting in numerical infeasibility issues. To overcome this limitation, this article proposes a novel scalable and reliable control scheme for dc microgrids. Initially, a general model for dc microgrids is established to enhance reliability, considering scenarios involving loss of control effectiveness (LoCE) and offset faults.

Secure Adaptive Event-Triggered Control for Cyber-Physical Power Systems Under Denial-of-Service Attacks.

Secure control for cyber-physical power systems (CPPSs) under cyber attacks is a challenging issue. Existing event-triggered control schemes are generally difficult to mitigate the impact of cyber attacks and improve communication efficiency simultaneously. To solve such two problems, this article studies secure adaptive event-triggered control for the CPPSs under energy-limited denial-of-service (DoS) attacks.

Differential Human Learning Optimization Algorithm.

Human Learning Optimization (HLO) is an efficient metaheuristic algorithm in which three learning operators, i.e., the random learning operator, the individual learning operator, and the social learning operator, are developed to search for optima by mimicking the learning behaviors of humans.

Cross-dimensional formation control of second-order heterogeneous multi-agent systems.

This paper is concerned with the cross-dimensional formation control of a second-order multi-dimensional heterogeneous multi-agent system. Agents are first separated into several groups according to their position/velocity vector dimensions. Then the cross-dimensional formation control problem is formulated such that agents in the same group form a time-varying formation in their own dimension and agents in different groups cooperatively move in multiple dimensions.

Secure Control of Networked Control Systems Using Dynamic Watermarking.

We here investigate the secure control of networked control systems developing a new dynamic watermarking (DW) scheme. First, the weaknesses of the conventional DW scheme are revealed, and the tradeoff between the effectiveness of false data injection attack (FDIA) detection and system performance loss is analyzed. Second, we propose a new DW scheme, and its attack detection capability is interrogated using the additive distortion power of a closed-loop system.

Distributed Fusion Estimation for Stochastic Uncertain Systems With Network-Induced Complexity and Multiple Noise.

This article investigates an issue of distributed fusion estimation under network-induced complexity and stochastic parameter uncertainties. First, a novel signal selection method based on event trigger is developed to handle network-induced packet dropouts, as well as packet disorders resulting from random transmission delays, where the H/H performance of the system is analyzed in different noise environments. In addition, a linear delay compensation strategy is further employed for solving the complex network-induced problem, which may deteriorate system performance.

Real-Time H Control of Networked Inverted Pendulum Visual Servo Systems.

Aiming at the challenges of networked visual servo control systems, which rarely consider network communication duration and image processing computational cost simultaneously, we here propose a novel platform for networked inverted pendulum visual servo control using H analysis. Unlike most of the existing methods that usually ignore computational costs involved in measuring, actuating, and controlling, we design a novel event-triggered sampling mechanism that applies a new closed-loop strategy to dealing with networked inverted pendulum visual servo systems of multiple time-varying delays and computational errors. Using the Lyapunov stability theory, we prove that the proposed system can achieve stability whilst compromising image-induced computational and network-induced delays and system performance.

Impact of PHEV in active distribution network under gas station network attack.

This paper proposes a novel method to analyze the impacts of plug-in hybrid electric vehicle (PHEV) charging on branch power flows and voltages of an active distribution network under gas station network attack. Specifically, when the gas station network is attacked and cannot provide refueling service, PHEVs running out of gasoline will be only driven in the electric vehicle (EV) mode, which will significantly increase PHEV charging load and lead to branch power flow increment and voltage drop or even voltage collapse in distribution network. To overcome the problem, the switch of PHEV operating mode (i.

A Multipopulation-Based Multiobjective Evolutionary Algorithm.

Multipopulation is an effective optimization component often embedded into evolutionary algorithms to solve optimization problems. In this paper, a new multipopulation-based multiobjective genetic algorithm (MOGA) is proposed, which uses a unique cross-subpopulation migration process inspired by biological processes to share information between subpopulations. Then, a Markov model of the proposed multipopulation MOGA is derived, the first of its kind, which provides an exact mathematical model for each possible population occurring simultaneously with multiple objectives.

Network-Based T-S Fuzzy Dynamic Positioning Controller Design for Unmanned Marine Vehicles.

This paper is concerned with a Takagi-Sugeno (T-S) fuzzy dynamic positioning controller design for an unmanned marine vehicle (UMV) in network environments. Network-based T-S fuzzy dynamic positioning system (DPS) models for the UMV are first established. Then, stability and stabilization criteria are derived by taking into consideration an asynchronous difference between the normalized membership function of the T-S fuzzy DPS and that of the controller.

Statistical Mechanics Approximation of Biogeography-Based Optimization.

Biogeography-based optimization (BBO) is an evolutionary algorithm inspired by biogeography, which is the study of the migration of species between habitats. This paper derives a mathematical description of the dynamics of BBO based on ideas from statistical mechanics. Rather than trying to exactly predict the evolution of the population, statistical mechanics methods describe the evolution of statistical properties of the population fitness.

Adaptive bacteria colony picking in unstructured environments using intensity histogram and unascertained LS-SVM classifier.

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images.