Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems.

Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of high-order nonlinear multiagent systems. The control algorithm can guarantee that all signals of the multiagent system are semi-globally uniformly ultimately bounded and all outputs can synchronously track a reference signal to a desired accuracy. A simulation example is carried out to further demonstrate the effectiveness of the proposed consensus control method.

Fuzzy neural network-based adaptive control for a class of uncertain nonlinear stochastic systems.

This paper studies an adaptive tracking control for a class of nonlinear stochastic systems with unknown functions. The considered systems are in the nonaffine pure-feedback form, and it is the first to control this class of systems with stochastic disturbances. The fuzzy-neural networks are used to approximate unknown functions. Based on the backstepping design technique, the controllers and the adaptation laws are obtained. Compared to most of the existing stochastic systems, the proposed control algorithm has fewer adjustable parameters and thus, it can reduce online computation load. By using Lyapunov analysis, it is proven that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded in probability and the system output tracks the reference signal to a bounded compact set. The simulation example is given to illustrate the effectiveness of the proposed control algorithm.

Adaptive neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems.

This brief studies an adaptive neural output feedback tracking control of uncertain nonlinear multi-input-multi-output (MIMO) systems in the discrete-time form. The considered MIMO systems are composed of n subsystems with the couplings of inputs and states among subsystems. In order to solve the noncausal problem and decouple the couplings, it needs to transform the systems into a predictor form. The higher order neural networks are utilized to approximate the desired controllers. By using Lyapunov analysis, it is proven that all the signals in the closed-loop system is the semi-globally uniformly ultimately bounded and the output errors converge to a compact set. In contrast to the existing results, the advantage of the scheme is that the number of the adjustable parameters is highly reduced. The effectiveness of the scheme is verified by a simulation example.

Who donates blood at five ethnically and geographically diverse blood centers in China in 2008.

BACKGROUND: In China recruitment and retention of sufficient numbers of safe blood donors continues to be a challenge. Understanding who donates blood, particularly those who donate larger (>200 mL) whole blood (WB) units, will help blood centers to target more effective recruitment and retention strategies. STUDY DESIGN AND METHODS: Demographic characteristics of 226,489 allogeneic WB donors from January to December 2008 at five geographically and ethnically diverse, urban blood centers were analyzed. RESULTS: The typical Chinese WB donor can be characterized as first-time volunteer (67.9%), male (56.9%), less than 45 years old (93.8%), and Han ethnicity (86.1%). Most donors had some college or below educational level (77.5%), donated at a mobile collection site (97.6%), and donated 300- or 400-mL units (76.0%). Differences in WB volume donations and donor demographics exist among the five centers. CONCLUSION: In China compared to the United States, donations are made by younger donors and donors give infrequently and make smaller WB donations. To help ensure supply adequacy, continued efforts are needed to have donors give larger volumes of WB in China.

A multi-Chinese blood center study testing serologic-negative donor samples for hepatitis C virus and human immunodeficiency virus with nucleic acid testing.

BACKGROUND: A multi-blood center study was conducted to evaluate a human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) multiplex nucleic acid testing (NAT) donor screening test and to determine the residual risk for HIV-1 and HCV infection. STUDY DESIGN AND METHODS: A commercially available HIV-1 and HCV assay (Procleix, Chiron Corp.) was used for simultaneous detection of HIV-1 RNA and HCV RNA on 89,647 unlinked donor samples. NAT was performed with pools of 16 samples that had passed all routine screening tests. Single-donor NAT was performed for samples that had been disqualified by any reactive screening test result(s). Anti-HCV (Ortho third-generation HCV enzyme immunoassay [EIA]), alanine aminotransferase, and HCV NAT (Roche COBAS Amplicor HCV test) confirmatory tests were used for HCV EIA-nonreactive, HCV NAT-reactive samples. RESULTS: Three HCV NAT yield cases and no HIV-1 yield cases were detected. The yield rate for HCV NAT was 3.4 per 10(5) (95 percent confidence interval [CI], 0.7-9.8). The estimated incidence rate for HCV is 24.2 per 100,000 person-years (95% CI, 3.4-88.0). If minipool NAT is added to routine donor screening, the residual risk for HCV is estimated to be reduced to 1 in 20.4x10(4) (95% CI, 1 in 5.2x10(4)-1 in 165.5x10(4)). CONCLUSION: The residual risk for transfusion-transmitted HCV infection is still relatively high in China. Incorporating NAT technology into blood donor screening would be estimated to reduce the residual risk of HCV infections eightfold over current EIA screening.