Switching Signals Research Articles

Model-based temporal unmixing towards quantitative photo-switching optoacoustic tomography

Optoacoustic (OA) imaging combined with reversibly photoswitchable proteins has emerged as a promising technology for the high-sensitivity and multiplexed imaging of cells in live tissues in preclinical research. Through carefully designed illumination schedules of ON and OFF laser pulses, the resulting OA signal is a multiplex of different reporter species and the background. We propose a model-based variational framework to computationally unmix and image different species of photo-switching reporters using optoacoustic tomography. It is based on a detailed mathematical description of the photo-switching mechanism, which models how relevant physical parameters such as the kinetic constants and light fluence impact the switching signal. We introduce an algorithm that operates on images, as opposed to traditional pixelwise approaches. It takes the form of an iterative inversion combined with tailored ℓ1 and total-variation regularization to increase the robustness to noise and to improve the unmixing quality. We show that our method can disentangle multiple spatially overlapping labels and recover continuous maps of quantities of interest on controlled phantoms and mice experiments.

A broadcast-and-select ROADM architecture to support linear hub-ended trees using point-to-multipoint coherent transceivers [Invited

Point-to-multipoint (P2MP) coherent pluggable transceivers based on digital subcarrier multiplexing (DSCM) have been proposed as a promising technology to reduce the costs of optical transport networks. However, to establish the P2MP trees, bidirectional multicast functionality is required at the optical nodes. While conventional broadcast-and-select (B&S) wavelength selective switch (WSS)-based reconfigurable optical add/drop multiplexer (ROADM) architectures can inherently perform splitting operations, merge operations of DSCM signals face internal blocking in conventional WSSs since they require switching signals from different input ports on the same carrier wavelength (although using different subcarriers) to the common output port. In this paper, we propose an alternative ROADM architecture requiring a simple low-cost modification, which can support P2MP trees, provided that they are routed as linear chains with the hub node at one end, without requiring multicast-enabled WSSs. We evaluate the potential savings of linear hub-ended P2MP trees on a metro reference scenario using a modified tree-determination, routing, and spectrum assignment (TRSA) dimensioning algorithm. Results indicate that linear hub-ended trees can significantly reduce transceiver costs with respect to point-to-point (P2P) solutions in all considered cases, with savings ranging from 6%–28% depending on the traffic load. While these savings are somewhat less than those achievable with arbitrary P2MP trees and latency is slightly higher, spectrum waste is reduced by employing linear routing, and the trees can be supported by the proposed architecture.

Data-driven stabilization of switched and constrained linear systems

We consider the design of state feedback control laws for both the switching signal and the continuous input of an unknown switched linear system, given past noisy input-state trajectories measurements. Based on Lyapunov–Metzler inequalities and on a matrix S-lemma, we derive data-dependent bilinear programs, whose solution directly returns a provably stabilizing controller and ensures H2 or H∞ performance. We further present relaxations that considerably reduce the computational cost, still without requiring stabilizability of any of the switching modes. Finally, we showcase the flexibility of our approach on the constrained stabilization problem for an unknown perturbed linear system. We validate our theoretical findings numerically, demonstrating the favorable trade-off between conservatism and tractability achieved by the proposed relaxations.

A Cross-Layer Game-Theoretic Approach to Resilient Control of Networked Switched Systems Against DoS Attacks.

This article investigates the resilient control strategies of networked switched systems (NSSs) against denial-of-service (DoS) attacks and external disturbance. In the network layer, both the defender and the attacker allocate energy over multiple channels. Considering the impact of switching characteristic in the physical layer on the network layer, a dynamic regulating factor is proposed to adjust the total energy of the defender. To optimize the signal-to-interference-noise ratio and energy consumption simultaneously at each player's side, a multiobjective game problem is formulated. Furthermore, a nondominated sorting genetic algorithm framework is employed, incorporating the knee point selection mechanism to attain the Pareto-Nash equilibrium, based on which the optimal defense strategy can be derived to achieve resilience against DoS attacks. In the physical-layer, taking the dynamic packet loss caused by DoS attacks and external disturbance into account, an H∞ minimax controller containing control inputs and the switching signal is designed to guarantee the optimal performance for NSSs through the dynamic game-theoretic approach. Finally, the networked continuous stirred tank reactor system is provided to verify the effectiveness of the proposed method.

Adaptive Neural Control Approach for Switched Nonlinear Discrete‐Time Systems With Actuator Faults and Input Dead Zone

In this paper, an adaptive control strategy is developed for discrete‐time switched nonlinear systems with actuator faults and dead‐zone input under arbitrary switching conditions. The actuator faults considered include loss‐of‐effectiveness and bias faults, which are unknown but bounded. The complex structure of these systems, combined with actuator faults and dead‐zone inputs, presents significant challenges for control and this problem is addressed by approximating the unknown functions of each subsystem using radial basis function neural networks. Under arbitrary switching signals, the suggested controller and adaptive laws ensure that all signals remain bounded and the system output tracks the reference signal with a small bounded tracking error. The efficiency of the control technique is proven by two numerical examples.

A Novel 49-Level Inverter Topology with Reduced Component Count and Total Standing Voltage for PV Energy Systems

This paper introduces a novel 49 Level (49-L) inverter topology designed to overcome the limitations of traditional inverters in photovoltaic (PV) renewable energy systems. This design focuses on minimizing component count and total standing voltage (TSV) at high output levels, making it versatile for various applications. The proposed inverter incorporates a modified packed H-Bridge unit and basic units to optimize component usage and reduce switch voltage stress. Mathematical formulations for calculating switching angles are provided, simplifying switching signal generation and reducing processing requirements. The 49-level inverter undergoes rigorous testing under different load conditions, with analysis emphasizing key performance metrics such as total harmonic distortion (THD), switch voltage stress, TSV, and efficiency. Its suitability for PV system integration - particularly in standalone systems - is demonstrated, highlighting its potential for renewable energy applications. The obtained results unveil that the proposed inverter achieves low THD for voltage and current, meeting IEEE 519 standards. The voltage THD is found to be at the value of 1.66% under all loads. The current THD is found to be at 1.66% under resistive load and ranges from 0.11% to 0.14% under RL loads. Moreover, the inverter's efficiency - depending on load conditions - is found to range from 96% to 98%. Additionally, the proposed inverter performs well under dynamic conditions, with smooth transitions during changes in irradiation levels and load types. Furthermore, this topology is the most cost-effective compared to other recent multilevel inverter (MLI) designs. Finally, the proposed 49-level inverter offers a promising solution for PV renewable energy systems, delivering high power quality, efficiency, and flexibility.

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. This protocol incorporates weight estimation of a radial basis function neural network (RBFNN) and introduces two internal dynamic variables. Following the Lyapunov's theory, sufficient criteria are established for ensuring the mean-square exponential stability of the resulting system. Additionally, an SMC scheme based on the convergence factor is designed to fulfill reachability conditions. Finally, two examples are carried out to validate the solvability and applicability of the attained control methodology.

Comparative analysis of different types of pulse width modulation techniques for multilevel inverters

Multilevel inverters have gained significant attention in recent years due to their ability to achieve higher voltage and lower harmonic distortion compared to conventional two-level inverters. Pulse width modulation (PWM) techniques play a crucial role in controlling multilevel inverters by generating the required switching signals for their power electronic devices. This paper presents a comprehensive comparative analysis of various PWM techniques employed in multilevel inverters, including sinusoidal pulse width modulation (SPWM), space vector pulse width modulation (SVPWM), carrier-based pulse width modulation (CBPWM), and selective harmonic elimination (SHEPWM). Each PWM technique's advantages, limitations, and suitability for different multilevel inverter topologies are discussed. Furthermore, recent advancements and hybrid PWM techniques are also examined to explore potential improvements in performance and efficiency. This paper aims to provide researchers, engineers, and practitioners with valuable insights into selecting the most appropriate PWM technique for their specific multilevel inverter applications, considering factors such as performance requirements, cost constraints, and ease of implementation.

Design of Two Phase DC-AC Interleaved Boost Inverter with Voltage Control System using PI Controller

DC-DC Interleaved Boost Converter (DC-DC IBC) topology was developed through the interleaving technique since conventional DC-DC Boost Converter has many problems related to complex circuit control, harmonics, and output power. In this research, DC-DC IBC was developed into a Two-Phase AC-AC Interleaved Boost Converter (TP AC-AC IBC), then combined with a Two-Phase Full Bridge Inverter to become a Two-Phase DC-AC Interleaved Boost Inverter (TP DC-AC IBI). TP DC-AC IBI has several advantages, including minimal current and voltage ripples and greater output power because it consists of two AC-AC IBCs. This research aims to meet highly regulated AC voltage needs with the renewable energy source input using the proposed topology, by implementing Proportional Integral (PI) close loop control system. The output voltage is detected using a voltage transducer LV-25P, then compared with a reference voltage and controlled using a PI controller to keep the output voltage consistently stable. The switching signal setting uses the Sinusoidal Pulse Width Modulation (SPWM) technique by modulating the control output with a high frequency. As a verification step, testing was carried out using Power Simulator (PSIM) software and then validated by hardware testing in the laboratory. Testing was carried out using several test signals, and it was found that the proposed method worked well. System efficiency and Total Harmonic Distortion (THD) tests carried out using various load values, and a maximum efficiency of 93.87% and a minimum THD of 2.46% were obtained.

Iterative learning consensus control for switched discrete-time multi-agent systems based on the 2-D linear discrete model

In this article, a class of switched nonlinear discrete-time heterogeneous (NDTH) multi-agent systems (MASs) with switching signals in both agent dynamics and communication topologies are considered, and a distributed iterative learning control (ILC) law is proposed for the output consensus of the switched NDTH MAS so that the outputs of all follower agents can well track the leader agent. With the proposed ILC controller, the iterative learning dynamic process of the switched NDTH MAS is firstly formulated as a two-dimensional (2-D) linear discrete Roesser model with specified boundary states at each switching sub-interval. Afterwards, according to the exploited properties on solution of the 2-D linear discrete Roesser model, a sufficient convergence theorem for the presented ILC controller is derived. At last, the validity of the ILC-based consensus controller is illustrated through a simulation experiment.

Decentralized Finite‐Time Adaptive Neural Output‐Feedback Quantized Control for Switched Nonlinear Large‐Scale Delayed Systems

ABSTRACTThis paper considers the problem of decentralized finite‐time adaptive neural output‐feedback quantized control for a class of switched nonlinear large‐scale delayed systems. A switched high‐gain quantized state observer is therefore constructed for each subsystem to estimate unavailable system states. Different from the traditional Lyapunov–Krasovskii functional method, multiple Lyapunov–Krasovskii functions are introduced to develop the decentralized adaptive output‐feedback control strategy with neural network approximation for the switched nonlinear large‐scale delayed systems. Under a category of switching signals with persistent dwell time, all signals in the closed‐loop switched system are semi‐globally uniformly ultimate bounded. Meanwhile, the tracking errors can remain in a small domain of origin in finite time. Case studies are finally used to illustrate the flexibility and effectiveness of the proposed control approach, including the switched two continuous stirred tank reactor delayed systems.

Full‐Order and Reduced‐Order H∞ Filtering Syntheses of Uncertain Switched Systems via Event‐Triggered Strategy

ABSTRACTVia event‐triggered strategy, full‐order and reduced‐order filtering syntheses are addressed for uncertain switched systems in the paper. Norm‐bounded uncertainty is considered in each switched subsystem. An event‐triggered strategy is primarily specified to determine whether the information of an uncertain switched system is transmitted or not. Full‐order and reduced‐order filters are considered on account of the outputs of the proposed event‐triggered strategy. By the merging switching signal technique, it can be established as a switched filtering error system with uncertain switched systems. Some sufficient conditions are subsequently presented to ensure exponential stability (ES) with weighted performance for the filtering error system. Moreover, some devised methods of full‐order and reduced‐order filters are also given, and therefore filters with different orders can be selected according to different needs in practical applications. A lower bound more than zero is found to exclude Zeno behavior on the event‐triggered intervals. Finally, the validity and feasibility of this study are illustrated by a practical example.

Real Time Traffic Management System Using Machine Learning

The increasing quantity of automobiles on the road presents difficulties for conventional traffic control strategies. With heavy traffic levels, these traditional methods find it difficult to handle. They only work well in light traffic situations; when there is a large difference in traffic volume on one side of the road or when vehicle density increases on one side, they are unable to adjust. Therefore, by adding dynamic signal switching capabilities, we want to modernise the static signal system. The updated system will continuously check and modify the timing of the signals in real time. In this project, we want to use real-time image detection to precisely measure traffic density and figure out the best times to switch signals, especially when traffic is heavy. Putting this strategy into practice should effectively reduce traffic jams and accelerate traffic flow.

A Modular Track and Signaling Simulation Trainer for Railway Technology Program

The modular railway track and signaling simulation trainer research project was developed to provide an enjoyable and educational tool to train railway students and professionals upon recognizing the need for effective training in traffic and signaling safety-critical areas. It provides a miniature model that accurately replicates railway switch points and signaling systems with modules depicting track layouts and signaling conditions created using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). The prototype's accurate and efficient miniature railway model showed that the simulation trainer was very effective. The survey demonstrated that railway students and professionals were satisfied with the trainer's performance and various use and educational potential for students. This simulation trainer design successfully changes railway training programs because it offers a relatively safe and exciting environment that allows learners to get practical experience and understanding of railway operations. The modular design of the trainer will facilitate future expansion and customization, making it adaptable to railway training needs and technology. The simulation trainer should include level crossings, track circuits, and train detection systems for further investigation. This would provide an improvement in the comprehensiveness and flexibility of the trainer, therefore helping with providing skilled railway workers.

Effective magnetic switching of terahertz signals in planar structured spintronic emitters

Effective magnetic switching of terahertz signals in planar structured spintronic emitters

Fault Estimation and Tolerant Anti‐Disturbance Switching Control for Switched Systems With Its Application to Circuit Systems

ABSTRACTThis study proposes a fault estimation and tolerant anti‐disturbance switching control (ADSC) approach for the switched systems subject to the system fault and multiple disturbances. The fault dose not required to have a model. The disturbances contain the modeled unmeasurable part and the unmodeled measurable part. First, a composite switching estimator is constructed to simultaneously estimate the unavailable system state, fault and modeled disturbance. Then, by means of the estimator, a switching controller is developed to tolerant the fault and complement the modeled disturbance. Further, under the average dwell time relevant switching signals, criteria are established to ensure the fault estimation performance and robustness property for the switched systems. Finally, via implementing the presented fault estimation and tolerant ADSC scheme on a switched circuit system to regulate the charge and flux, the reasonability of the established result is verified.

Dual-site responsive module-triggered CRISPR/Cas12a switch with enhanced reaction kinetics for specific detection of PSA

Despite advances in DNA-based nanodevices for tumor biomarker detection, the pursuit of enhanced sensitivity and specificity remains a profound challenge. In this study, we designed an integrated dual-site responsive module as the AND logic gate that responded to both prostate-specific antigen (PSA) and apurinic/apyrimidinic endonuclease 1 (APE1), triggering a tetrahedral DNA nanostructure (TDN)-accelerated CRISPR/Cas12a signal switch for PSA detection. In detail, the dual-site responsive module was a T-shaped probe comprised of three DNA strands, which contained PSA aptamer and apurinic/apyrimidinic (AP) sites, significantly improving the specificity of prostate cancer screening by orthogonal recognition of PSA and APE1. When both PSA and APE1 were present, PSA could specifically bind with the aptamer, while APE1 catalyzed and cleaved the AP sites, releasing a part of one auxiliary strand as the mimic target (MT). To enhance the trans-cleavage efficiency of the CRISPR/Cas12a signal switch, we parallelly constructed the TDN with extended non-target strands (NTS) at each vertex, which could capture the MT to form double-stranded DNA (dsDNA) activators at the TDN vertices (TDN-activators) for triggering the CRISPR/Cas12a signal switch. Benefiting from the rigid framework of TDN, the TDN-activators not only increased the local concentration of Cas12a but also enabled a dominant conformation that was more favorable for recognizing and activating the Cas12a-crRNA complex, which demonstrated a 4.06-fold increase in trans-cleavage efficiency compared to that of dsDNA-activated Cas12a. This work applies the T-shaped probes and TDN-accelerated CRISPR/Cas12a signal switch to achieve the specific and sensitive electrochemiluminescence (ECL) detection of PSA from 1.0 × 10−5 to 10 μg/mL with a low limit of detection (LOD) of 4.5 × 10−6 μg/mL, offering a promising tool for early clinical screening of prostate cancer.

An a-IGZO TFT Based Pixel Circuit Suitable for Stable Operation Under Amoled Impulsive Driving Dimming Scheme

Active matrix organic light emitting diode (AMOLED) display backplanes based on amorphous indium-gallium-zinc oxide (a-IGZO) TFTs have gained considerable attention [1]-[3], due to their large on-off ratio, extremely low off-current, and low-temperature fabrication process [4]-[6].In mobile AMOLED displays, AMOLED impulsive driving (AID) dimming scheme is required to finely tune the overall brightness of the display [7]. This AID dimming modifies the off-duty ratio of the emission (EM) signal of the pixel circuit according to ambient light conditions, thereby regulating the brightness scale of the screen. Consequently, the phase of the EM signal is altered more than once during one frame [8].However, the multiple switching of the EM signal within a single frame can lead to undesired voltage loss in capacitors responsible for storing the threshold voltage (VTH) of a driving transistor and the data voltage related to the luminance of OLED. Such voltage loss ultimately results in luminance non-uniformity of the display, especially in low gray levels [9]. Therefore, it is important to design a pixel circuit minimizing the effect of luminance distortion under repetitive switching.In this work, we proposed a pixel circuit based on a-IGZO TFTs, comprising 6 transistors and 2 capacitors (6T2C). The schematic of the proposed pixel circuit is shown in Figure 1(a). Transistor 1 (T1) serves as the driving transistor, supplying current to the OLED, while T2 to T6 are the switching transistors. Because only the source node of the driving transistor is affected by the EM signal, additional voltage loss in capacitors caused by several switching operations can be diminished. Furthermore, two capacitors are employed to mitigate low compensation accuracy due to the short addressing time under a high refresh rate (e.g., 1.9 μs for 240 Hz refresh rate with a UHD resolution (3080 x 2160) display). Hence, the proposed pixel circuit shows stable operation under the AID dimming scheme.Figure 1(b) shows the HSPICE simulation result of the OLED current error rate degradation before and after implementing the AID dimming. The proposed circuit is compared with a-IGZO TFT based 7T2C pixel circuit, which the EM signal affects both the gate and source nodes of the driving transistor [3]. The current error rate of the 7T2C pixel circuit increased by over half at lower gray levels when the AID dimming was applied. In contrast, the proposed pixel circuit showed negligible variation in current error rate across all gray levels after adopting the AID dimming scheme.The simulation result indicates the proposed pixel circuit can maintain the luminance uniformity under the AID dimming without additional compensation. This demonstrates the potential for the development of mobile AMOLED display backplane technologies based on a-IGZO TFTs.

Fault Diagnosis Method for Converter Stations Based on Fault Area Identification and Evidence Information Fusion.

DC converter stations have a high voltage level, a long transmission distance, and complex internal equipment, and contain power electronic devices, which seriously endanger the stable operation of the system itself and the active distribution network at the receiving end when faults occur. Accurate fault analysis and diagnosis are critical to the safe and stable operation of power systems. Traditional fault diagnosis methods often rely on a single source of information, leading to issues such as insufficient information utilization and incomplete diagnostic scope when applied to DC transmission systems. To address these problems, a fault diagnosis method for converter stations based on preliminary identification of the fault range and the fusion of evidence information of the switch signal and electrical quantity is proposed. First, the preprocessing of converter station sequential event recording (SER) events and a statistical analysis of event characteristics are completed to initially determine the range of the fault.Then, a fuzzy Petri net model and a BP neural network model are constructed on the basis of the fault data from a real-time digital simulation system (RTDS), and the corresponding evidence information of the switch signal and electrical quantity are obtained via iterative inference and deep learning methods. Finally, on the basis of D-S evidence theory, a comprehensive diagnosis result is obtained by fusing the switch and electric evidence information. Taking the fault data of a DC converter station as an example, the proposed method is analyzed and compared with the traditional method, which is based on single information. The results show that the proposed method can reliably and accurately identify fault points in the protected area of the converter station.

Bumpless transfer control of switched systems: A dynamic event-triggering switching control approach

This paper studies the bumpless transfer (BT) control issue for switched systems with event-triggered (ET) control input. The aim is to reduce the jumps in control input at both switching and triggering points, while capturing the stability of the switched systems. First, a dynamic ET program is constructed with the triggering condition based on the level of suppression of input signal jumps. This not only reduces input jumps at triggering points, but also prevents Zeno behavior caused by triggering within the operation time interval of subsystems. Second, a sampled state-dependent switching signal is designed to ensure a dwell time for subsystems to prevent Zeno phenomenon induced by switching. Further, a switched ET controller with alleviated jumps is designed. Third, conditions are obtained to simultaneously reach both stabilization and BT of switched systems. Finally, the effectiveness of the theoretical results is demonstrated through a simulation of an engine model.