Fault diagnosis based on adaptive observer for a class of non-linear systems with unknown parameters

In this paper, the fault diagnosis problem for a class of non-linear systems with uncertainty which depends on states, inputs and unknown constant parameters is discussed. Under some geometric conditions, the system is transformed into two different subsystems. One is not affected by actuator faults, so a non-linear adaptive observer can be designed based on the assumption of the strictly positive realness (SPR). The other whose states can be measured is affected by the faults. Actuator fault diagnosis is based on estimations of both the state and the unknown parameters with good accuracy. Discussions on release of SPR requirement and extension to the sensor fault case are also made. Finally, two examples are given in order to illustrate the applicability of the proposed methods for actuator fault diagnosis and sensor fault diagnosis respectively.     

Industrie 4.0

Industry 4.0 – Challenges for constructions of vacuum systems Vacuum systems are finding their way into branches and belonging modern process chains which were hardly in contact with UHV technology in the past. Besides an automatic operation and a flawless processing of parts, vacuum systems and their peripheral devices have to feature options for data output and analysis for subsequent processing in e.g. MES to come up with Industry 4.0 requirements. Subcomponents in vacuum technology partly comply with these requirements in a insufficient way because of their unchanged demands over the last decades. This makes integration into an automatic system more difficult. Despite of that, Industry 4.0 compliant vacuum systems are already producible when there's access to high-level experiences in vacuum and automation technology. This is shown by the examples of residual gas analysis and cleanliness measurement systems and the vacuum bake out oven. A cooperation of vacuum system manufacturers and manufacturers of components is necessary in the future to be able to produce automated vacuum systems in a more efficient way.     

Phototemtide A,a Cyclic Lipopeptide Heterologously Expressed from Photorhabdus temperata Meg1, Shows Selective Antiprotozoal Activity

A new cyclic lipopeptide, phototemtide A ( 1 ), was isolated from Escherichia coli expressing the biosynthetic gene cluster pttABC from Photorhabdus temperata Meg1. The structure of 1 was elucidated by HR-ESI-MS and NMR experiments. The absolute configurations of amino acids and 3-hydroxyoctanoic acid in 1 were determined by using the advanced Marfey's method and comparison after total synthesis of 1 , respectively. Additionally, three new minor derivatives, phototemtides B–D ( 2 – 4 ), were identified by detailed HPLC–MS analysis. Phototemtide A ( 1 ) showed weak antiprotozoal activity against Plasmodium falciparum, with an IC₅₀ value of 9.8 μm . The biosynthesis of phototemtides A–D ( 1 – 4 ) was also proposed.     

Computing the Output Distribution and Selection Probabilities of a Stack Filter from the DNF of Its Positive Boolean Function

Many nonlinear filters used in practise are stack filters. An algorithm is presented which calculates the output distribution of an arbitrary stack filter S from the disjunctive normal form (DNF) of its underlying positive Boolean function (PBF). Our algorithm avoids to enumerate the models of the PBF one by one, and thus is considerably more efficient than previous methods. The so called rank selection probabilities can be computed along the way.