Fadaptive Backstepping Control of Active Magnetic Bearings

A new control methodology, adaptive backstepping control (ABC), is applied to a linearized model of an active magnetic bearing (AMB). Our control objective is to regulate the deviation of the magnetic bearing from its equilibrium position in the presence of an external disturbance. The control approach is based on adaptive backstepping control, which is a combination of a recursive Lyapunov controller and adaptive laws. In this thesis, two types of adaptive backstepping methods are used. The first method is based on full-state feedback, for which all three states in the linearized AMB model (velocity, position, and current) are used to construct the control law. The second method is adaptive observer-based backstepping control (AOBC) where only one feedback signal (position) is employed. An exponentially convergent estimator is developed for the second adaptive controller to observe other states. It is proved that the adaptive backstepping controlled AMB system is asymptotically stable around the system\u27s equilibrium point. Simulation results demonstrate fast and stable system response. They also verify the effectiveness and robustness of the adaptive backstepping control methods against external disturbances and system parameter variation

Adaptive Control of an Active Magnetic Bearing with External Disturbance

Adaptive back stepping control (ABC) is originally applied to a linearized model of an active magnetic bearing (AMB) system. Our control goal is to regulate the deviation of the magnetic bearing from its equilibrium position in the presence of an external disturbance and system uncertainties. Two types of ABC methods are developed on the AMB system. One is based on full state feedback, for which displacement, velocity, and current states are assumed available. The other one is adaptive observer based back stepping controller (AOBC) where only displacement output is measurable. An observer is designed for AOBC to estimate velocity and current states of AMB. Lyapunov approach proves the stabilities of both regular ABC and AOBC. Simulation results demonstrate the effectiveness and robustness of two controllers

Investigation and identification of the first mushroom poisoning case caused by Amanita sychnopyramis f. subannulata in Jiangxi

Objective To investigate and identify a case caused by mushroom poisoning in May 2019 in Jiangxi Province. Methods The case was studied with the epidemiological information, clinical data, and suspicious mushroom samples were identified by morphological and molecular studies. Results The epidemiological information showed that all the patients had eaten different quantity of mushrooms which were picked and boiled by themselves, the average incubation period was 2.5 hours, and the symptoms of dizziness, gastrointestinal discomfort, vomiting, numbness of limbs and so on had existed orderly of the patients. The morphological and molecular studies identified the samples were Amanita sychnopyramis f. subannulata. Conclusion The incident was the first reported case caused by Amanita sychnopyramis f. subannulata in Jiangxi Province. The poisonous mushroom species can be identified combined with epidemiology, morphology and molecular studies. The situation of s mushroom poisoning in Jiangxi Province is still serious and the relevant departments should strengthen prevention and control

Analysis of nontyphoidal Salmonella clinical isolates antibiotic resistance based on whole genome sequencing in Jiangxi Province in 2018

Objective Understanding of bacterial antibiotic resistance is the basis for guiding clinical anti-infective therapy and monitoring antimicrobial resistance trends. The study was aimed to investigate the antibiotic resistance characteristics of nontyphoidal Salmonella isolates from foodborne disease cases in Jiangxi Province in 2018, study the correlations between resistance phenotypes and genotypes, and evaluate the application prospects of whole genome sequencing (WGS) in antimicrobial resistance surveillance. Methods In this study, 58 nontyphoidal Salmonella strains were isolated from foodborne disease patients in Jiangxi Province in 2018 and were tested for susceptibility to 14 antimicrobials using broth microdilution. The 58 isolates were subjected to WGS, and resistance genes were identified from assembled sequences that compared with ResFinder database. Results 77.59% (45/58) of isolates were resistant to tetracycline, and 72.41% (42/58) were resistant to ampicillin. 100.00% of isolates were susceptible to imipenem. 56.90% (33/58) of isolates displayed resistance to at least 3 classes of antibiotics, and 3.45% (2/58) of isolates had resistance to at least 6 of 8 classes tested. A total of 47 unique resistance genes referred to 11 classes of antibiotics, plus mutations in gyrA, gyrB and parC structural of quinolone resistance-determining region (QRDR), were identified. 100.00% (58/58) of isolates had aminoglycoside resistance genes, and 72.41% (42/58) of isolates harboured tetracycline resistance genes. Macrolide resistance genes were presented in 3.45% (2/58) of isolates. 77.59% (45/58) of isolates were contained at least 3 classes of antibiotics resistance genes, and 1.72% (1/58) of isolates harboured at least 9 classes of resistance genes. The overall resistance genotypes and phenotypes were consistent in 93.43% (611/654) of cases. Except quinolones, the correlations were above 91% for tested antibiotics. Correlations were 100% for some classes of antibiotics. Conclusion The antibiotic resistance phenomenon of these isolates was serious. The resistance phenotypes were in good accordance with genotypes, and WGS can be used as an effective tool to predict the antibiotic resistance of nontyphoidal Salmonella. As more new antibiotic resistance genes were discovered, the consistency of resistance genotypes and phenotypes will be further improved

Fadaptive Backstepping Control of Active Magnetic Bearings

A new control methodology, adaptive backstepping control (ABC), is applied to a linearized model of an active magnetic bearing (AMB). Our control objective is to regulate the deviation of the magnetic bearing from its equilibrium position in the presence of an external disturbance. The control approach is based on adaptive backstepping control, which is a combination of a recursive Lyapunov controller and adaptive laws. In this thesis, two types of adaptive backstepping methods are used. The first method is based on full-state feedback, for which all three states in the linearized AMB model (velocity, position, and current) are used to construct the control law. The second method is adaptive observer-based backstepping control (AOBC) where only one feedback signal (position) is employed. An exponentially convergent estimator is developed for the second adaptive controller to observe other states. It is proved that the adaptive backstepping controlled AMB system is asymptotically stable around the system\u27s equilibrium point. Simulation results demonstrate fast and stable system response. They also verify the effectiveness and robustness of the adaptive backstepping control methods against external disturbances and system parameter variation

Adaptive Back-stepping Control of Active Magnetic Bearings

An adaptive back-stepping control (ABC) is originally applied to a linearized model of an active magnetic bearing (AMB) system. Our control objective is to regulate the deviation of the magnetic bearing from its equilibrium position in the presences of an external disturbance and system uncertainties. The ABC consists of a recursive Lyapunov controller and adaptive laws. It is based on full-state feedback, for which all three states in the linearized AMB model (velocity, position, and current) are estimated to construct the control law. It is proved that the adaptive back-stepping controlled AMB system is asymptotically stable around the system\u27s equilibrium points. Simulation results verify the effectiveness and robustness of the ABC against external disturbances and system uncertainties

Adaptive Back-stepping Control of Active Magnetic Bearings

An adaptive back-stepping control (ABC) is originally applied to a linearized model of an active magnetic bearing (AMB) system. Our control objective is to regulate the deviation of the magnetic bearing from its equilibrium position in the presences of an external disturbance and system uncertainties. The ABC consists of a recursive Lyapunov controller and adaptive laws. It is based on full-state feedback, for which all three states in the linearized AMB model (velocity, position, and current) are estimated to construct the control law. It is proved that the adaptive back-stepping controlled AMB system is asymptotically stable around the system\u27s equilibrium points. Simulation results verify the effectiveness and robustness of the ABC against external disturbances and system uncertainties