Switching Signals Research Articles

Improved results of asynchronous mixed [formula omitted] and passive control for discrete-time linear switched system with mode-dependent average dwell time

This paper primarily discusses the hybrid H∞ and passive control problems of asynchronous discrete-time switching systems based on mode-dependent average dwell time. In the process of analysis, we divide the running time of the subsystem into two cases: matching and not matching the controller. Firstly, we employ the method of mode-dependent average dwell time to model the system and derive a suitable switching signal, ensuring the system is global uniform asymptotic stability. Meanwhile, the weighted hybrid H∞ and passivity are achieved. Then, according to the different performance parameters of each subsystem, the appropriate controller is designed using the form of linear matrix inequalities to improve the stability of the system. Finally, the effectiveness of the proposed method is demonstrated by a numerical example and a population ecosystem.

Vliyanie shuma na rezistivnoe pereklyuchenie memristora na osnove stabilizirovannogo dioksida tsirkoniya

The effect of Gaussian noise on the switching of a ZrO2(Y) based memristor from the low resistance state (LRS) into the high resistance state (HRS) including transitions from the LRS into intermediate metastable states has been studied. The series of positive (with addition of the noise signal or without the one) and negative rectangular voltage pulses were used as the switching signals. The adding of noise to the switching signal initiated the switching of the memristor from the LRS into the HRS at smaller pulse magnitudes than in the case of switching by the rectangular pulses without adding the noise. A necessary (preset) HRS can be achieved passing the intermediate states by adding the noise with certain parameters to the rectangular switching pulses. The resistive switching is performed without application of adaptive switching protocols. The results of the present study can be applied in the development of innovative memristor switching protocols.

Some Theoretical Aspects of the Neural Network Approach to Stabilization of Switched Interval Systems

We consider the problem of stabilization of a switched interval linear system with slow switchings that are inaccessible to observation. It is proposed to look for a solution in the class of variable structure controllers. To ensure the functionality of such a controller, it is necessary to construct an observer of the switching signal. This paper is devoted to some theoretical issues related to the period of quantization of the neural observer’s operating time.

Split-spectrum based distributed state estimation for linear systems

This paper studies a distributed state estimation problem for both continuous- and discrete-time linear systems. A simply structured distributed estimator {comprising interconnected local estimators} is first described for estimating the state of a continuous and multi-channel linear system whose sensed outputs are distributed across a fixed multi-agent network. The estimator is then extended to non-stationary networks whose graphs switch according to a switching signal. The estimator is guaranteed to solve the problem, provided a network-widely shared high gain condition achieving a form of spectrum separation is satisfied. As an alternative to sharing a common gain across the network, a fully distributed version of the estimator is also studied in which each agent adaptively adjusts a local gain, though the practicality of this approach is subject to a robustness issue common to adaptive control. A discrete-time version of the distributed state estimation problem is also studied, and a corresponding estimator based again on spectrum separation, but not high gain, is proposed for time-varying networks. For each scenario, it is explained how to construct the estimator so that the state estimation errors in the local estimators all converge to zero exponentially fast at a fixed but arbitrarily chosen rate, provided the network’s graph is strongly connected for all time. The proposed estimators are inherently resilient to abrupt changes in the number of agents and communication links in the inter-agent communication graph upon which the algorithms depend, provided the network is redundantly strongly connected and redundantly jointly observable.

Disturbance-observer-based control for non-homogeneous semi-Markov jump systems with time-varying delays

This paper discusses the issue of disturbance-observer-based control (DOBC) for a kind of continuous-time non-homogeneous semi-Markov jump systems (SMJSs) with time-varying delays. Unlike the existing results, the system examined in this article is about non-homogeneous SMJSs, which indicates that its transition rates (TRs) is time-varying. The versions of TRs matrices are selected by a switching signal, which is independent of the semi-Markov process that decides on the system modes. The time-varying TRs are established to be of two situations: stochastic process and arbitrary switching, respectively. First, we construct a novel class of Lyapunov function that is related to both system mode and switching signal mode, thus it can make more use of information about the system and help reduce conservatism. Second, some conditions are given to guarantee the exponentially mean square stable of the SMJSs and H∞ output tracking performance index. Finally, two examples are provided to demonstrate the efficacy of research methods.

Dynamic observer‐based fault estimation and fault‐tolerant control for switched stochastic systems with multiple faults

AbstractThe fault estimation (FE) and fault‐tolerant control (FTC) problems are studied for the switched system with sensor fault, actuator fault, and stochastic noise. The dynamic FE observers are used to reconstruct the system states and faults at the same time. Differently from the classical observer design method, in the process of observers design, both the output information and its derivative are introduced to improve the estimation performance, especially in the case of the systems subject time‐varying fault. Based on the coordinate transformation, the output derivative is not appeared in the observers, which means that the proposed dynamic observers can be used for the cased that the output derivative is unmeasured. Utilizing the estimate information, the observer‐based FTC scheme is given. For any switching signal, the linear matrix inequality (LMI) conditions are provided, which can ensure that the entire system is mean‐square exponentially stable (MSES). Finally, simulation examples show the effectiveness of the observer and controller.

Mode-Independent Switching Stabilizing Control for Continuous-Time Linear Markovian Switching Systems

We present a switching control approach to studying the stabilization problem of linear Markovian switching systems. The switching signal in feedback loop is generated independently of the underlying switching signal. Moreover, the closed-loop switching signal can be accelerated to show the influence of its stationary distribution. As a result, the transition matrix of the closed-loop system approximates such an operator semigroup that its infinitesimal generator exactly is the combination of the closed-loop subsystem matrices with respect to this stationary distribution. Therefore, endowing this infinitesimal generator with certain stable structure may allow us to make the closed-loop system exponentially stable at the expense of fast switching speed.

Design of 3-Level T-type NPC Inverter for EV Applications

In recent years, there has been a significant demand for lightweight converters that provide exceptional control performance while generating minimal acoustic noise. This has resulted in higher switching signals for hard- switched 2-level low voltage 3-phase inverters. However, the increased switching frequencies have a negative impact on the inverters’ efficiency, requiring the use of expensive switch technology to maintain high efficiency. This paper aims to tackle these challenges by introducing the design and implementation of a extremely effective 3-Level T-Type Neutral Point Clamped (NPC) inverter designed for Electric Vehicle (EV) applications. 3-Level T-Type NPC inverter associates the strengths of both NPC and T-Type inverters. Similar towards the NPC, it offers a lower breakdown voltage for the switching devices, thereby reducing switching losses. Additionally, it shares the characteristics of the T-Type inverter, resulting in fewer conduction losses. To validate the feasibility of the converter, simulation is performed using MATLAB software, followed by the development and testing of a lab-scale prototype. The proposed three-level T-type NPC inverter have several merits over traditional 2-level inverters, including reduced distortion, switching losses, and improved efficiency. These benefits contribute to enhanced motor drive performance, reduced electromagnetic interference (EMI), and extended battery life in EVs.

Reduced switch cascaded asymmetrical 27 level inverter-STATCOMwith fuzzy logic controller

<p>In this study, a 27-levelinverter with a reduced switch asymmetrical cascaded H-bridge (CHB) with fuzzy logic controller (FLC) is proposed. With series connections, a low voltage converter, a middle level voltage converter, and a high voltage converter make up the static synchronous compensator (STATCOM). The configuration of the asymmetrical inverter uses trinary DCsources. To acquire switching signals for the trinary inverter-based STATCOM to compensate for real power, load voltage, reactive power, load current, and power factor under load changing conditions, FLC is constructed. With fewer switches, the suggested arrangement produces greater voltage levels. The performance of the reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with FLCis simulated using the MATLAB Simulink platform under both static and dynamic load conditions. When compared to reduced switch asymmetrical cascaded H-bridge inverter-STATCOM with traditional proportional integral (PI) controller, the FLC result demonstrates efficient unbalanced load compensation. The FLC in the proposed inverter also lowers the total harmonic distortion.</p>

Outlier-Resistant State Estimation for Singularly Perturbed Complex Networks With Nonhomogeneous Sojourn Probabilities.

This study investigates an outlier-resistant state estimation problem for singularly perturbed complex networks (SPCNs) with sojourn probabilities and randomly occurring coupling strengths. Aiming at better describing the dynamic behavior of the network topology for SPCNs, a novel switching law associated with the time-varying sojourn probabilities is developed, and the variation of sojourn probabilities is arranged by a high-level deterministic switching signal. Meanwhile, a sequence of mode-dependent variables is employed to describe the randomly occurring coupling strength. Subsequently, to alleviate the side effects from possible measurement outliers, a dynamic saturation function-based state estimator is designed, whose saturation level is adaptively varying based on previous estimation errors. In virtue of Lyapunov theory and mode-dependent average dwell-time strategy, it can be verified that the resulting dynamics is stochastic H∞ finite-time bounded. To this end, a simulation example is presented to show the validity of the proposed estimator design method.

Investigation of Non-Stationary Characteristics of Signal Switching Devices of Information-Measuring Systems with Dissimilar Devices

Investigation of Non-Stationary Characteristics of Signal Switching Devices of Information-Measuring Systems with Dissimilar Devices

Parallel Monitoring of Measurable Residual Disease and Chimerism By NGS in Myelodysplastic Syndrome after Allogenic STEM Cell Transplant

Background: Minimal Residual Disease (MRD) and chimerism monitoring in patients with Myelodysplastic Syndrome (MDS) is essential to track and quantify the proportion of donor and recipient cells to assess engraftment and treatment efficacy. Next Generation Sequencing (NGS) is rapidly evolving, can identify several somatic mutations simultaneously, quantifies allele burden, and is a suitable technology for this task. Traditionally its main limitations have been high single base error rates, which limited the sensibility to 0.1-1% Variant Allele Frequency (VAF). However, sensitivities up to 10 -4 VAF can be achieved by applying novel ultrasensitive personalized sequencing techniques. Aims: This study explores the applicability of PhasedSNP, a deep sequencing approach that quantifies chimerism in parallel to MRD in MDS patients after Allogenic Stem Cell Transplantation (ASCT). Methods: We included 24 patients older than 18 years who underwent ASCT between 2015 and 2022 at four third-level hospitals. We excluded patients with missing follow-up due to procedure-related mortality or relapse before day 100 and patients with unavailable samples. Fifty-three post-transplant samples were sequenced (six at day +30; two at +60; 21 at +100; 21 at +180, and three at day +360). Seven additional pre-transplant samples were included to confirm the donor and receptor signal switch. The genomic DNA of the donor and receptor was sequenced with an in-house PhasedSNP panel that covers 58 regions with paired polymorphisms in less than 15bp. Receptor DNA was also sequenced with a 42-gene panel (Ion Torrent TM) to identify somatic mutations used as biomarkers in follow-up samples to quantify MRD as previously described in ( Onecha E. et al. Haematologica 2019). Briefly, an amplicon-multiplexed mini-panel was defined for every patient to detect the selected MRD biomarkers and donor/receptor phased SNPs identified at diagnosis. The mini-panel included molecular-tagged primer pairs to amplify every selected marker (PhasedSNPs and somatic mutations) in three biological replicates. Final libraries were sequenced on the Ion S5 System platform with a median coverage of 211,190 reads per amplicon. A median of 558 ng of genomic DNA (range 73.44 - 858.6 ng) was sequenced in follow-up cases. Results: After excluding potential CHIP and Germline mutations, the most frequently mutated genes in the cohort were STAG2 (21%), SETBP1TP53RUNX1 andETV6 (16% each one). The baseline genotyping permitted to identify at least one somatic MRD biomarker in 79% of the patients (19/24), and 50% (12/24) presented more than one somatic mutation. MRD could be calculated for 42 of 53 samples. Thirteen patients presented sample at day +180 and clinical information. Four of them progressed, being three of them MRD positive. At this time-point the sensitivity of the test was 75% and the negative predictive value of 86%. The baseline PhasedSNP panel identified chimerism biomarkers (donor and receptor) for all patients. The PhasedSNP chimerism test presented a dynamic detection range below 10 -5 in serial dilutions. The test was positive for 48/53 samples using a threshold of 10 -4, with an average signal of 7·10 -3 (range 2·10 -5 to 4·10 -2). The correlation between PhasedSNP chimerism and MRD was high (R=0.921, p<0.001). However, the chimerism signal was consistently above the MRD signal, most likely due to the detection of healthy receptor cells with the PhasedSNP test. This can be seen in the two examples presented in the figure, with one patient ( MDS7, Figure, top) with an equivalent signal of chimerism at days +30, +100, and +180, but with MRD negativity at day +420 and two logarithms reduction in chimerism compared the highest value (day 100). Regarding the other patient, MDS13 ( Figure, bottom), chimerism and MRD dynamics evolve parallel but with more than two logarithmic differences between both values. This patient was MRD negative at day +100, but positive at day +180, and relapses one year later. Summary/Conclusion: NGS-based parallel detection of chimerism and MRD in MDS is feasible and has high applicability and sensitivity, with several advantages compared to traditional methods. Nevertheless, further research and a larger cohort is necessary to draw meaningful conclusions.

MSC converter with optimized input current ripple for fuel cells applications

This article focuses on the analysis of a newly introduced DC-DC converter structure suitable for applications in fuel cell generation systems, the Modified Series Capacitor (MSC) converter. An interleaved-type converter with high voltage gain. The converter was proposed with a particular PWM scheme in which their two transistors operate with equal duty cycle, but the switching signals are 180° out of phase, and it uses two equal inductors. This article suggests a different way to design and operate the MSC converter with unequal inductors and unequal duty cycles. The primary benefit of the proposed approach with independent duty cycles and inductances is that it allows for the application of a numerical optimization algorithm to minimize the converter's input current ripple without the need to increase the stored energy in inductors. For example, it was possible to reduce one of the two inductors while maintaining (or even improving) the power quality of the input current. To prove the concept, an experiment was set up, executed, and confirmed.

Graph-based conditions for feedback stabilization of switched and LPV systems

This paper presents novel stabilizability conditions for switched linear systems with arbitrary and uncontrollable underlying switching signals. We distinguish and study two particular settings: (i) the robust case, in which the active mode is completely unknown and unobservable, and (ii) the mode-dependent case, in which the controller depends on the current active switching mode. The technical developments are based on graph-theory tools, relying in particular on the path-complete Lyapunov functions framework. The main idea is to use directed and labeled graphs to encode Lyapunov inequalities to design robust and mode-dependent piecewise linear state-feedback controllers. This results in novel and flexible conditions, with the particular feature of being in the form of linear matrix inequalities (LMIs). Our technique thus provides a first controller-design strategy allowing piecewise linear feedback maps and piecewise quadratic (control) Lyapunov functions by means of semidefinite programming. Numerical examples illustrate the application of the proposed techniques, the relations between the graph order, the robustness, and the performance of the closed loop.

Switched linear singular systems in discrete time: Solution theory and observability notions

We study the solution theory of linear switched singular systems. In a recent paper by Anh et al. (2019), it was highlighted that the common assumption that each mode of the switched system is index-1 is not sufficient to guarantee existence and uniqueness of solutions of the corresponding switched system and the notion of “jointly index-1” was introduced. However, until now it was not clear what conditions are actually required to guarantee existence and uniqueness of solutions if the switching signal is not considered arbitrary. In particular, we study the two relevant situations where the mode sequence is fixed (and the switching times are arbitrary) and where the whole switching signal is fixed. In both cases, we provide conditions in terms of the original system matrices which ensure existence and uniqueness of solutions. We also extend the idea of the one-step map introduced by Anh et al. (2019) to these two cases. It turns out that in the case of a fixed switching signal, the index-1 condition for the individual modes is also not necessary (in addition to not being sufficient). Furthermore, we utilize the established solution theory to provide characterizations of observability and determinability of switched singular systems.

Research and Implementation of a Demodulation Switch Signal Phase Alignment System in Dynamic Environments.

In the space gravitational wave detection mission, inertial sensors play the role of providing an inertial reference for the laser interferometric measurement system. Among them, the capacitance sensor serves as the core key technology of the inertial sensor, used to measure the relative position of the test mass (TM) in the electrode cage. The capacitance sensor utilizes synchronous demodulation technology to extract signals from the AC induction signal. When the phase of the demodulation switch signal is aligned, the synchronous demodulator can most effectively filter out noise, thus directly influencing the performance of the capacitance sensor. However, since the TM is in a suspended state, the information read by the capacitance sensor is dynamic, which increases the difficulty of demodulation phase alignment. In light of this, a method is proposed for achieving the phase alignment of the demodulation switch signal in a dynamic environment. This is accomplished by adjusting the phase of the demodulation switch signal, and subsequently computing the phase difference between the AC induction signal and the demodulation switch signal. At the same time, a measurement and evaluation method for phase deviation is also proposed. Ultimately, an automatic phase alignment system for the demodulation switch signal in dynamic environments is successfully implemented on an FPGA platform, and tests are conducted on a hexapod PI console platform to simulate dynamic environments. The experimental results demonstrate that the system accurately achieves phase alignment in the static environment, with a phase deviation of 0.1394 rad. In the simulated dynamic environment, the phase deviation is 0.1395 rad.

A selection principle of submodule switching state vectors for switching frequency reduction in voltage self‐balancing half‐bridge modular multilevel converters

AbstractThe problem of submodule switching frequency reduction in half‐bridge modular multilevel converters (HB‐MMCs) with capacitor voltage self‐balancing control is considered and explored in this paper. A selection principle of submodule switching state vectors is proposed based on the voltage self‐balancing switching state matrix, aiming to lower submodule switching frequency and device losses. The relationship between system stability and submodule switching signals is revealed according to the capacitor voltage self‐balancing characteristics, and the full‐rank constraints on the voltage self‐balancing switching state matrix are proposed. Considering the tradeoff between switching loss and capacitor voltage fluctuation, the evaluation indexes of voltage self‐balancing control effect are determined. The selection principle of submodule switching state vectors and the optimized construction method of switching state matrix are presented. Voltage self‐balancing HB‐MMC models are built in MATLAB/Simulink, and it is verified that the submodule switching state vector selection principle proposed in this study can effectively reduce switching frequency while meeting the evaluation requirements of practical engineering projects, so as to achieve the balance between switching loss and steady‐state capacitor voltage fluctuation.

Distributed consensus tracking of nonlinear MASs under stochastic switching topologies via aperiodically intermittent control

SummaryIn this article, we investigate the mean‐square consensus tracking problem of nonlinear MASs subjected to external disturbances under stochastic switching topologies. An aperiodically intermittent control strategy is proposed to guarantee consensus tracking in the mean‐square sense, which depends only on the local state information of the neighbors and the leader. The stochastic switching signal of the interaction topologies is modeled as a continuous‐time Markov process, and the aperiodically intermittent control method is driven by a discrete‐time series of stochastic samples, that are independent of each other. Moreover, several sufficient conditions are established to ensure the feasibility of the control strategy. The proofs are given by employing matrix inequality theory and Lyapunov stability theory. Finally, numerical simulations are provided to verify the feasibility of the proposed theoretical results.

Model Predictive Control of Switched Reluctance Machines for Suppressing Torque and Source Current Ripples Under Bus Voltage Fluctuation

This article presents a novel model predictive method for torque ripple and source current ripple suppression in switched reluctance machines (SRMs) when the bus voltage fluctuates. Based on the measured rotor position, phase current, and phase voltage, the states, including bus voltage, capacitor current, and phase flux-linkage, are calculated for the preparation of the prediction. On this basis, the machine torque and inverter current for all the possible switching states are predicted to construct the cost function. The operating state with the minimum value of cost function is considered as the optimal switch signal and applied to the control power converter, thus achieving the effect of simultaneous reduction of torque ripple and source current ripple. Experimental results show the proposed method has a significant effect on the suppression of both torque ripple and source current ripple even with bus voltage fluctuation, which verifies the effectiveness of the proposed method. The influence of the key factors, such prediction horizon, parametric variation, and weight coefficient, on the machine performance are further investigated. The proposed method is easy to be implemented in the control logic as well as robust to bus voltage fluctuations, enabling to promote the competitiveness of SRMs in electric vehicle application.

A Delay Classification-Based Approach to Distributed Consensus of Nonlinear Time-Delay Multiagent Systems

This paper investigates the problem of the fixed directed topology-based leader-following consensus control for nonlinear multiagent systems with output delays. Diverging from existing results, this study focuses on large time-varying output delay. Taking this condition into account, a novel delay classification-based distributed output feedback consensus algorithm is developed. First, we divide the output delay into two types through a designed constant and introduce a switching signal to distinguish these two types. Then, we build a distributed compensator for each follower using relevant outputs to reconstitute the leader-following tracking errors. This compensator relies on the output delay and is irrelevant to the nonlinear dynamics of the system. Then, we design a distributed linear controller for each follower with the compensator's assistance. Subsequently, a new unified Lyapunov-Krasovskii functional is developed to prove that all agents can realize leader-following full-state consensus with the action of the controller. We also provide sufficient conditions to demonstrate the controller's validity. Finally, a simulation example is supplied to validate the efficiency of our algorithm.