Global Event-Triggered Funnel Control of Switched Nonlinear Systems via Switching Multiple Lyapunov Functions.

In this article, the global event-triggered (ET) funnel tracking control problem is studied for a class of switched nonlinear systems with structural uncertainties, where the solvability of the control problem for each subsystem is not needed. A switching multiple Lyapunov functions (MLFs) method is established, where MLFs are designed to handle switched inverse dynamics, and a switching barrier Lyapunov function is constructed to address switched sampled errors that may compromise system stability. This is achieved alongside a new switching dynamic event-triggering mechanism (DETM). By combining this method with backstepping, a dwell-time state-dependent switching law and an ET funnel controller of each subsystem are constructed, effectively eliminating the issue of the "explosion of complexity" encountered in traditional backstepping without using dynamic surface control or command filters. Additionally, the designed switching DETM ensures that the tracking error always evolves within a performance funnel in any consecutive triggering interval, excluding Zeno behavior, and guaranteeing positive constant lower bounds for two consecutive triggering intervals and any switching interval, respectively. Finally, an example is provided to show the validity of the theoretical results.

A Dual Triggering Scheme to Adaptive Fuzzy Resilient Control of Switched Nonlinear Systems Against Mixed Attacks.

A dual event-triggered adaptive fuzzy resilient control scheme for a class of switched nonlinear systems with vanishing control gains under mixed attacks is proposed in this article. The scheme proposed achieves dual triggering in the channels of sensor-to-controller and controller-to-actuator by designing two new switching dynamic event-triggering mechanisms (ETMs). An adjustable positive lower bound of interevent times for each ETM is found to preclude Zeno behavior. Meanwhile, mixed attacks, that is, deception attacks on sampled state and controller data and dual random denial-of-service attacks on sampled switching signal data, are handled by constructing event-triggered adaptive fuzzy resilient controllers of subsystems. Compared with the existing works for switched systems with only single triggering, more complex asynchronous switching caused by dual triggering and mixed attacks and subsystem switching is addressed. Further, the obstacle caused by vanishing control gains at some points is eliminated by proposing an event-triggered state-dependent switching law and introducing vanishing control gains into a switching dynamic ETM. Finally, a mass-spring-damper system and a switched RLC circuit system are applied to verify the obtained result.

Investigating the impact of inter-limb asymmetry in hamstring strength on jump, sprint, and strength performance in young athletes: comparing the role of gross force.

The main purpose of this cross-sectional study was to examine the impact of the inter-limb asymmetry of hamstring strength on jump, sprint and strength performance and to compare the effects of inter-limb asymmetry of hamstring strength with gross force (GF) of the hamstring on these physical qualities in youth volleyball athletes. Eighty-one youth volleyball players (age: 16.6 ± 1.9 years; training experience: 3.0 ± 0.9 years; height: 191.4 ± 7.1 cm; body mass: 78.5 ± 12.9 kg; lean body mass: 63.5 ± 10.5 kg; body fat rate: 18.6% ± 6.1%) performed a mid-season battery of tests consisting of morphological test, depth jump (DJ), counter movement jump (CMJ), squat jump (SJ), 10 m sprint, isometric mid-thigh pull (IMTP) and hamstring strength test. All tests reported good to excellent reliability (ICC range = 0.815-0.996) and acceptable variability (CV range = 3.26-7.84%). Results show a significant negative relationship between inter-limb asymmetry of hamstring strength and all physical qualities (r = -0.271 to -0.445; p < 0.05), and a significant positive relationship between GF of hamstring and all physical qualities (r = 0.303 to 0.664; p < 0.05). Additionally, GF of hamstring was more relevant to IMTP-PF (peak force) (r = 0.664) and inter-limb asymmetry of hamstring strength was more relevant to 10 m sprint (r = -0.445). The findings from this study indicate that, for youth athletes, the GF of the hamstring is crucial for overall lower limb strength performance, and the importance of inter-limb symmetry of hamstring strength increases with the complexity of the task.

Dynamic Event-Triggered Adaptive NN Control for Switched Uncertain Nonlinear Systems.

This article is concerned with the problem of dynamic event-triggered adaptive neural network (NN) control for a class of switched strict-feedback uncertainty nonlinear systems. A novel switched command filter-based dynamic event-triggered adaptive NN control approach is set up by exploiting the backstepping and command filter and the common Lyapunov function method. Since adaptive controllers of subsystems are event triggered, then if the switching happens between any two consecutive triggering instants, asynchronous switching will arise between candidate controllers of subsystems and subsystems. Unlike the existing literature, where maximum asynchronous time is restricted, without any strict limitations on maximum asynchronous time being needed in this article, the asynchronous switching problem is directly handled by proposing a novel switching dynamic event-triggered mechanism (DETM) and event-triggered adaptive controllers of subsystems. Moreover, a piecewise constant variable is introduced into the switching DETM, which overcomes the difficulty of switched measurement error being discontinuous. Also, a strictly positive lower bound of interevent times is obtained. Finally, a continuous stirred tank reactor system and a numerical example are presented to demonstrate the effectiveness of the developed approach.

Safety-Critical Model Reference Adaptive Control of Switched Nonlinear Systems With Unsafe Subsystems: A State-Dependent Switching Approach.

In this article, a novel safety-critical model reference adaptive control approach is established to solve the safety control problem of switched uncertain nonlinear systems, where the safety of subsystems is unnecessary. The considered switched reference model consists of submodels possessing safe system behaviors that are governed by switching signals to achieve satisfactory performances. A state-dependent switching control technique based on the time-varying safe sets is proposed by utilizing the multiple Lyapunov functions method, which guarantees the state of the subsystem is within the corresponding safe set when the subsystem is activated. To deal with uncertainties, a switched adaptive controller with different update laws is constructed by resorting to the projection operator, which reduces the conservatism caused by the common update law adopted in all subsystems. Moreover, a sufficient condition is obtained by structuring a switched time-varying safety function, which ensures the safety of switched systems and the boundedness of error systems in the presence of uncertainties. As a special case, the safety control problem under arbitrary switching is considered and a corollary is deduced. Finally, a numerical example and a wing rock dynamics model are provided to verify the effectiveness of the developed approach.

Systematic evaluation of line probe assays for the diagnosis of tuberculosis and drug-resistant tuberculosis.

BACKGROUND: Line probe assays (LPAs) are PCR-based assays used for the rapid diagnosis of Mycobacterium tuberculosis (MTB) and drug-resistant tuberculosis (DR-TB). But studies on its performance are insufficient. Thus, in this study, we conducted a systematic review and meta-analysis to evaluate the effect of LPAs in the detection of MTB and drug-resistant TB in comparison with the traditional culture and DST methods. METHODS: A systemic literature search was conducted on the Web of Science, Embase, PubMed, the Cochrane Library, Scopus, and OVID databases. All the included studies were classified according to different detecting objects. Sensitivity, specificity, Positive Likely Ratio (PLR), Negative Likely Ratio (NLR), Diagnostic Odds Ratio (DOR), corresponding 95% confidence interval, Area Under Curve (AUC), Deeks' funnel plot, and Bivariate Boxplot was used to do the evaluation. RESULTS: 147 studies included 491 datasets, with 182,448 samples, were incorporated into our analysis. The sensitivity (95% CI), specificity (95% CI), PLR, NLR, DOR and AUC for MTB were 0.89 (0.86 to 0.92), 0.94 (0.90 to 0.97), 15.70, 0.11, 139 and 0.96, respectively; for rifampicin-resistant TB were 0.96 (0.95 to 0.97), 0.99 (0.98 to 0.99), 82.9, 0.04, 1994 and 1.00, respectively; for isoniazid-resistant TB were 0.91 (0.89 to 0.93), 0.99 (0.98 to 0.99), 83.4, 0.09, (0.99 to 1.00), 195.7, 0.07, 2783 and 1.00, respectively; for Multi-drug resistant TB (MDR-TB) were 0.93 (0.90 to 0.95), 1.00 (0.99 to 1.00), 195.7, 0.07, 2783 and 1.00, respectively; for extensively drug-resistant TB (XDR-TB) were 0.60 (0.33 to 0.82), 1.00 (0.95 to 1.00), 291.3, 0.4, 726 and 0.95, respectively; for (second-line drug-resistant TB) SLID-TB were 0.83 (0.78 to 0.87), 0.98 (0.97 to 0.99), 44.6, 0.17, 262 and 0.98, respectively. Sensitivity in pre-extensively drug-resistant TB (Pre-XDR-TB) was 0.67, specificity was 0.91. No publication bias existed according to Deeks' funnel plot. CONCLUSION: High diagnosis performance was confirmed in LPAs for the diagnosis of MTB and drug-resistant TB. LPAs might be a good alternative to culture and DST in detecting MTB, RR-TB, INH-TB, XDR-TB, SLID-TB, and MDR-TB. While more studies were still needed to explore the diagnosis performance of LPAs for Pre-XDR TB.

Evaluation of GeneXpert EV assay for the rapid diagnosis of enteroviral meningitis: a systematic review and meta-analysis.

BACKGROUND: GeneXpert enterovirus Assay is a PCR-based assay for Enterovirus meningitis diagnosis. However, there is currently no research about the performance of GeneXpert enterovirus assay in the diagnosis of enterovirus meningitis. Thus, a systematic review and meta-analysis is significant on the topic. METHODS: Embase, Cochrane Library, Web of Science, and PubMed were systematically reviewed with retrieval types. Some criteria were used to filter the studies. Only studies published in English, that made a comparison between GeneXpert enterovirus assay and RT-PCR, and could be formulated in a 2*2 table, were included. The quality of the included studies was evaluated by QUADAS-2. The effect of the GeneXpert enterovirus assay was assessed by the Sensitivity, Specificity, Positive Likelihood Ratio, Negative Likelihood Ratio, Diagnosis Odds Ratio, and summary receiver operating characteristic (SROC) curve. Publication bias and heterogeneity were evaluated by the Deeks' funnel test and Bivariate Box plot respectively. RESULTS: 7 studies were recruited in the analysis. The Pooled Sensitivity was 0.96 [95% CI (0.94-0.97)], Pooled Specificity was 0.99 [95% CI (0.98-0.99)], Positive Likelihood Ratio was 130.46 [95% CI (35.79-475.58)], Negative Likelihood Ratio was 0.04 [95% CI (0.02-0.10)], and Diagnostic Odds Ratio was 3648.23 (95% CI [963.99-13,806.72)]. In SROC Curve, Area Under Curve (AUC) was 0.9980, and Q*= 0.9849. In Deeks' funnel test, the P-value was 0.807 (P > 0.05), indicating no publication bias. The Bivariate Box plot indicated no evident heterogeneity. CONCLUSIONS: The GeneXpert enterovirus assay demonstrated high diagnostic accuracy in diagnosing enterovirus meningitis.

Evaluation of the loop-mediated isothermal amplification assay for Staphylococcus aureus detection: a systematic review and meta-analysis.

BACKGROUND: Staphylococcus aureus can cause many diseases and even death. It's important to detect Staphylococcus aureus rapidly and reliably. The accuracy of a novel test named LAMP in detecting Staphylococcus aureus is unclear. Therefore, a systematic review and meta-analysis were conducted to evaluate the accuracy of the LAMP assay for Staphylococcus aureus detection. METHODS: Four databases were searched for relevant studies. Meta-DiSc 1.4.0 and Stata 12.0 were used for statistical analysis. At the same time, we used QUADAS-2 to assess the studies we included. Two groups of subgroup analysis were done to differentiate the diagnostic effects of various LAMP tests and in cases of different gold standards. RESULTS: 11 studies were identified and 19 2 × 2 contingency tables were extracted in our study. The results showed that both pooled sensitivity and specificity of the LAMP assay were 99% (95% CI 99-100). CONCLUSION: The LAMP assay demonstrated high sensitivity and specificity in diagnosing Staphylococcus aureus.

Small-Gain Technique-Based Adaptive NN Control for Switched Pure-Feedback Nonlinear Systems.

This paper focuses on the problem of adaptive neural networks (NNs) tracking control for a class of completely nonaffine switched pure-feedback uncertain nonlinear systems with switched reference model. A sufficient and necessary condition for the control problem to be solvable is derived by exploiting the common Lyapunov function (CLF) method, backstepping, input-to-state stability analysis, and the small-gain technique. Also, a small-gain technique-based adaptive NN control scheme is provided to avoid the designed difficulty caused by the construction of an overall CLF for the switched closed-loop system, which is usually required when studying the switched pure-feedback system. Adaptive NN controllers of individual subsystems are constructed to guarantee that all of the signals in the closed-loop system are semi-globally uniformly ultimately bounded under arbitrary switchings, and the tracking error converges to a small neighborhood of the origin. Two examples, which include a continuously stirred tank reactor system, are presented to demonstrate the effectiveness of the proposed design approach.

Switched-Observer-Based Adaptive Neural Control of MIMO Switched Nonlinear Systems With Unknown Control Gains.

In this paper, the problem of adaptive neural output-feedback control is addressed for a class of multi-input multioutput (MIMO) switched uncertain nonlinear systems with unknown control gains. Neural networks (NNs) are used to approximate unknown nonlinear functions. In order to avoid the conservativeness caused by adoption of a common observer for all subsystems, an MIMO NN switched observer is designed to estimate unmeasurable states. A new switched observer-based adaptive neural control technique for the problem studied is then provided by exploiting the classical average dwell time (ADT) method and the backstepping method and the Nussbaum gain technique. It effectively handles the obstacle about the coexistence of multiple Nussbaum-type function terms, and improves the classical ADT method, since the exponential decline property of Lyapunov functions for individual subsystems is no longer satisfied. It is shown that the technique proposed is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop system under a class of switching signals with ADT, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the approach proposed is illustrated by its application to a two inverted pendulum system.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.