Cascade Radical Cyclization of Propargylamines for Functionalized 3-Arylthioquinoline Formation.

A novel and efficient strategy for the direct synthesis of 3-arylthioquinoline derivatives via radical induced tandem cyclization of propargylamines with diaryl disulfides was developed. This protocol undergoes a cascade sulfuration/ cyclization/ oxidation/ aromatization pathway to afford the desired products in a broad substrate scope using readily available starting materials under mild conditions. Based on this strategy, we further modified 3-arylquinolines to obtain two novel deep blue fluorescent molecules, QLSCz and QLSTCz, with good optical properties through two-step synthesis by oxidation and electron donor modification.

Neural Network-Based Sliding Mode Control for Semi-Markov Jumping Systems With Singular Perturbation.

The primary focus of this article centers around the application of sliding mode control (SMC) to semi-Markov jumping systems, incorporating a dynamic event-triggered protocol (ETP) and singular perturbation. The underlying semi-Markov singularly perturbed systems (SMSPSs) exhibit mode switching behavior governed by a semi-Markov process, wherein the variation of this process is regulated by a deterministic switching signal. To simultaneously reduce the triggering rate and uphold the system performance, a novel parameter-based dynamic ETP is established.

Two-Layer Asynchronous Control for a Class of Nonlinear Jump Systems: An Interval Segmentation Approach.

This article proposes the two-layer asynchronous control scheme for a class of networked nonlinear jump systems. For the constructed system in a network environment, the data transmission may suffer from many restrictions, such as incomplete acceptable mode information and transition information, nonlinearity of system and inadequate bandwidth resources, etc. Then, the two-layer asynchronous controller is developed to stabilize the plant constructed by Takagi-Sugeno (T-S) fuzzy method and semi-Markov theory (SMT).

Indefinite Robust Linear Quadratic Optimal Regulator for Discrete-Time Uncertain Singular Markov Jump Systems.

The robust LQ optimal regulator problem for discrete-time uncertain singular Markov jump systems (SMJSs) is solved by introducing a new quadratic cost function established by the penalty function method, which combines the penalty function and the weighting matrices. First, the indefinite robust optimal regulator problem for uncertain SMJSs is transformed into the robust optimal regulator problem with positive definite weighting matrices for uncertain Markov jump systems (MJSs). The transformed robust LQ problem is settled by the robust least-squares method, and the condition of the existence and analytic form of the robust optimal regulator are proposed.

Event-Based Asynchronous H∞ Control for Nonhomogeneous Markov Jump Systems With Imperfect Transition Probabilities.

The event-based H control problem is investigated for a class of nonhomogeneous Markov jump systems (MJSs) with partially unknown transition probabilities (TPs). The MJS is characterized by a piecewise nonhomogeneous Markovian chain, where the switching of the system TP matrix is governed by a higher-level chain. A hidden Markov model (HMM) is employed to observe the system mode, which cannot always be correctly detected in practice.

Asynchronous Control of 2-D Markov Jump Roesser Systems With Nonideal Transition Probabilities.

This article intends to study the asynchronous control problem for 2-D Markov jump systems (MJSs) with nonideal transition probabilities (TPs) under the Roesser model. Two practical considerations motivate the current work. First, considering that the system mode cannot always be observed accurately, a hidden Markov model (HMM) is adopted to describe the relationship between the mismatched modes.

Functionalization of the Octahydro-Binaphthol Skeleton: A Universal Strategy for Directly Constructing D-A Type Axially Chiral Biphenyl Luminescent Molecules.

D-A type axially chiral biphenyl luminescent molecules are directly constructed through ingenious functionalization of the octahydro-binaphthol skeleton without optical resolution. The circularly polarized organic light-emitting diodes based on them display remarkable circularly polarized electroluminescence emission, a high luminance of >10 000 cd m, a maximum external quantum efficiency of 6.6%, and an extremely low-efficiency roll-off.

Pinning Asymptotic Observability of Distributed Boolean Networks.

Asymptotic observability of distributed Boolean networks (DBNs) is studied in this article. Via a parallel extension method, asymptotic observability of the original system is converted to reachability at a fixed point of the extended system. Based on the structure matrix of the extended system, a necessary and sufficient condition is presented for asymptotic observability.

Precise Regulation of Multiple Resonance Distribution Regions of a B,N-Embedded Polycyclic Aromatic Hydrocarbon to Customize Its BT2020 Green Emission.

Recently, boron (B)/nitrogen (N)-embedded polycyclic aromatic hydrocarbons (PAHs), characterized by multiple resonances (MR), have attracted significant attention owing to their remarkable features of efficient narrowband emissions with small full width at half maxima (FWHMs). However, developing ultra-narrowband pure-green emitters that comply with the Broadcast Service Television 2020 (BT2020) standard remains challenging. Precise regulation of the MR distribution regions allows simultaneously achieving the emission maximum, FWHM value, and spectral shape that satisfy the BT2020 standard.

Base Metal-Controlled Chemodivergent Cyclization of Propargylamines for the Atom-Economic Synthesis of Nitrogen Heterocycles.

Herein, a base metal-enabled chemodivergent cyclization of propargylamines for the atom-economic construction of nitrogen heterocycles has been developed. Due to the different modes of activation of metal to propargylamine, copper-catalyzed 6 cyclization generates functionalized 2-substitued quinoline-4-carboxylates, while iron-promoted cascade amino Claisen rearrangement, aromatization, and aza-Michael addition afford diverse 2-substituted indole-3-carboxylate derivatives. Excellent selectivity, broad functional group tolerance, mild conditions, and flexible late-stage functionalization illustrate the high efficiency and synthetic utility of this chemodivergent reaction.

Sequential -Formed Kukhtin-Ramirez Adduct and P(NMe)-Catalyzed -Phosphination of α-Dicarbonyls with P(O)-H.

-Phosphination of α-dicarbonyls via sequential formation of a Kukhtin-Ramirez adduct and a P(NMe)-catalyzed process has been exploited for the synthesis of α-phosphoryloxy carbonyls. A range of P(O)-H derivatives, including diarylphosphine oxides, arylphosphinates, and phosphinates, are competent candidates to be introduced into the α-dicarbonyls in this transformation, and various α-phosphoryloxy carbonyls are obtained. This approach possesses advantages of mild conditions, simple operations, atom economy, high efficiency, and gram-scale synthesis, which make it promising in the synthesis toolbox.

Synchronization of Coupled Neural Networks With Constant Time-Delay Using Sampled-Data Information.

In this article, a synchronization control method is studied for coupled neural networks (CNNs) with constant time delay using sampled-data information. A distributed control protocol relying on the sampled-data information of neighboring nodes is proposed. Lyapunov functional is constructed to analyze the synchronization of CNNs with constant time delay.

Cooperative Tracking Control for Nonlinear MASs Under Event-Triggered Communication.

The neural network-based adaptive backstepping method is an effective tool to solve the cooperative tracking problem for nonlinear multiagent systems (MASs). However, this method cannot be directly extended to the case without continuous communication. It is because the discontinuous communication results in discontinuous signals in this case, the standard backstepping method is inapplicable.

Protocol-Based Synchronization of Stochastic Jumping Inertial Neural Networks Under Image Encryption Application.

This work investigates the protocol-based synchronization of inertial neural networks (INNs) with stochastic semi-Markovian jumping parameters and image encryption application. The semi-Markovian jumping process is adopted to characterize INNs under sudden complex changes. To conserve the limited available network bandwidth, an adaptive event-driven protocol (AEDP) is developed in the corresponding semi-Markovian jumping INNs (S-MJINNs), which not only reduces the amount of data transmission but also avoids the Zeno phenomenon.

Hybrid triggering design for global attitude synchronization of networked rigid bodies.

This paper is devoted to dealing with the problem of global attitude synchronization for quaternion-based multiple rigid bodies, regardless of the general directed topologies of networks and arbitrary initial orientations of rigid bodies. A novel canonical quaternion is constructed to represent all physical attitudes of rigid bodies such that the pseudo-synchronization of their quaternion representations (namely, the quaternions' vector parts of all rigid bodies reach agreement on some identical value, whereas their scalar parts do not) can be precluded. Moreover, to reduce unnecessary communication requirements of rigid bodies, a hybrid triggering mechanism involving both the time regulation and neighbors' non-real-time information is proposed, with which a distributed protocol is developed by leveraging the constructed canonical quaternion.

Representation-Learning-Based CNN for Intelligent Attack Localization and Recovery of Cyber-Physical Power Systems.

Enabled by the advances in communication networks, computational units, and control systems, cyber-physical power systems (CPPSs) are anticipated to be complex and smart systems in which a large amount of data are generated, exchanged, and processed for various purposes. Due to these strong interactions, CPPSs will introduce new security vulnerabilities. To ensure secure operation and control of CPPSs, it is essential to detect the locations of the attacked measurements and remove the state bias caused by malicious cyber-attacks such as false data inject attack, jamming attack, denial of service attack, or hybrid attack.

Data-Driven-Based Cooperative Resilient Learning Method for Nonlinear MASs Under DoS Attacks.

In this article, we consider the cooperative tracking problem for a class of nonlinear multiagent systems (MASs) with unknown dynamics under denial-of-service (DoS) attacks. To solve such a problem, a hierarchical cooperative resilient learning method, which involves a distributed resilient observer and a decentralized learning controller, is introduced in this article. Due to the existence of communication layers in the hierarchical control architecture, it may lead to communication delays and DoS attacks.

Distributed Lebesgue Approximation Model for Distributed Continuous-Time Nonlinear Systems.

Approximation models play a crucial role in model-based methods, as they enhance both accuracy and computational efficiency. This article studies distributed and asynchronous discretized models to approach continuous-time nonlinear systems. The considered continuous-time system consists of some distributed but physically coupled nonlinear subsystems that exchange information.

Optimized Adaptive Fuzzy Security Control of Nonlinear Systems With Prescribed Tracking Performance.

This article studies the optimized fuzzy prescribed performance control problem for nonlinear nonstrict-feedback systems under denial-of-service (DoS) attacks. A fuzzy estimator is delicately designed to model the immeasurable system states in the presence of DoS attacks. To achieve the preset tracking performance, a simper prescribed performance error transformation is constructed considering the characteristics of DoS attacks, which helps obtain a novel Hamilton-Jacobi-Bellman equation to derive the optimized prescribed performance controller.

Neural network-based adaptive second-order sliding mode control for uncertain manipulator systems with input saturation.

In order to solve the trajectory tracking problem for robotic manipulators with dynamic uncertainty, external disturbance and input saturation, a novel second-order sliding mode control scheme based on neural network is proposed in this paper. First of all, a model-based second-order non-singular fast terminal sliding mode controller (SONFTSMC) is designed to overcome the chattering problem under the consideration of uncertain parameters. Then attention is focused on the scenario that all those nonlinear uncertainties are unknown, and a new fuzzy wavelet neural network (FWNN) is designed to estimate those unknown uncertainties via lumping them into one compounded uncertainty.

Nonlinear Disturbance Observer-Based Fault-Tolerant Sliding-Mode Control for 2-D Plane Vehicular Platoon With UTVFD and ANAS.

This article investigates a nonlinear disturbance observer (NDO)-based fault-tolerant sliding-mode control (SMC) for 2-D plane vehicular platoon systems subjected to actuator faults with unknown time-varying fault direction (UTVFD), asymmetric nonlinear actuator saturation (ANAS), nonlinear unmodeled dynamics, and unknown external disturbance. The Nussbaum-type function approach is adopted to solve the problem of actuator faults with UTVFD. The designed NDO not only can estimate the lumped disturbance accurately but also can reduce the control peaking and chattering phenomena caused by the Nussbaum-type function.

Model-Free Adaptive Resilient Control for Nonlinear CPSs With Aperiodic Jamming Attacks.

The problem of the model-free adaptive resilient control (MFARC) for nonlinear cyber-physical systems (CPSs) suffered from aperiodic jamming attacks is investigated in this article. First, the MFARC framework subject to aperiodic jamming attacks is established, and an intermediate variable method is introduced to avoid using the unavailable time-varying parameter and further eliminate an extra assumption on the sign limit of it. Then, a MFARC scheme is devised to track the desired output, where the problem of the tracking control can be transformed into solving a feasibility problem, and the controller parameters can be obtained with the aid of the linear matrix inequality technique.

Asynchronous Event-Triggered Output-Feedback Control of Singular Markov Jump Systems.

This study focused on the asynchronous event-triggered output-feedback controller design problem for discrete-time singular Markov jump systems (MJSs). A hidden Markov model (HMM) was employed to estimate the system mode, which cannot always be ideally detected in practice. Because the full state is also difficult to obtain in practical scenarios, an output-feedback control scheme was used.

Resilient Consensus of Multiagent Systems Under Collusive Attacks on Communication Links.

This article addresses the resilient consensus problem of multiagent systems subject to cyber attacks on communication links, where the attacks on different links may collude to maintain undetectable. For the case with noncollusive attacks on links, a distributed fixed-time observer is designed so that the attack on each link can be detected by the two associated agents. A necessary and sufficient condition is derived to ensure the isolation of attacked links and no mistaken isolation of normal ones.