Identification and output tracking control of Hammerstein systems through wireless networks

his paper investigates the identification and output tracking control of a class of Hammerstein systems through a wireless network within an integrated framework and the statistic characteristics of the wireless network are modelled using the inverse Gaussian cumulative distribution function. In the proposed framework, a new networked identification algorithm is proposed to compensate for the influence of the wireless network delays so as to acquire the more precise Hammerstein system model. Then, the identified model together with the model-based approach is used to design an output tracking controller. Mean square stability conditions are given using linear matrix inequalities (LMIs) and the optimal controller gains can be obtained by solving the corresponding optimization problem expressed using LMIs. Illustrative numerical simulation examples are given to demonstrate the effectiveness of our proposed method.

New results on stability analysis of delayed recurrent neural networks based on the integral quadratic constraints approach

This paper is concerned with the analysis of the stability of delayed recurrent neural networks. In contrast to the widely used Lyapunov–Krasovskii functional approach, a new method is developed within the integral quadratic constraints framework. To achieve this, several lemmas are first given to propose integral quadratic separators to characterize the original delayed neural network. With these, the network is then reformulated as a special form of feedback-interconnected system by choosing proper integral quadratic constraints. Finally, new stability criteria are established based on the proposed approach. Numerical examples are given to illustrate the effectiveness of the new approach.

Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

Detection of Bridge Dynamic Parameters using an Instrumented Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles

Efficacy of Wind Power in Mitigation of CO2 Emission from the Irish Electrical Grid

The results in this paper are based on a data set containing system demand, wind generation and CO2 emission between Jan 2010 and Sep 2013. The data was recorded at 15 minute intervals and reflects the macroscopic operation of the Republic of Ireland's electrical grid. The data was analyzed by investigating how daily wind generation effected daily CO2 emission across multiple days with equivalent daily demand. A figure for wind turbine efficiency was determined by dividing the CO2 mitigation potential of wind power by the CO2 intensity of the grid; both in units of Tonnes of CO2 per MWh. The yearly wind power efficiency appears to have increased by 5.6% per year, now standing around 90%. Over the four years significant regularity was observed in the profiles of wind turbine efficiency against daily demand. It appears that the efficiency profile has moved in recent years so that maximum efficiency coincides with most frequent demand.

Immunohistochemistry should undergo robust validation equivalent to that of molecular diagnostics

Immunohistochemistry (IHC) is a widely available and highly utilised tool in diagnostic histopathology and is used to guide treatment options as well as provide prognostic information. IHC is subjected to qualitative and subjective assessment, which has been criticised for a lack of stringency, while PCR-based molecular diagnostic validations by comparison are regarded as very rigorous. It is essential that IHC tests are validated through evidence-based procedures. With the move to ISO15189 (2012), not just of the accuracy, specificity and reproducibility of each test need to be determined and managed, but also the degree of uncertainty and the delivery of such tests. The recent update to ISO 15189 (2012) states that it is appropriate to consider the potential uncertainty of measurement of the value obtained in the laboratory and how that may impact on prognostic or predictive thresholds. In order to highlight the problems surrounding IHC validity, we reviewed the measurement of Ki67and p53 in the literature. Both of these biomarkers have been incorporated into clinical care by pathology laboratories worldwide. The variation seen appears excessive even when measuring centrally stained slides from the same cases. We therefore propose in this paper to establish the basis on which IHC laboratories can bring the same level of robust validation seen in the molecular pathology laboratories and the principles applied to all routine IHC tests.

Test-retest variability in structural and functional parameters of glaucoma damage in the glaucoma imaging longitudinal study.

PURPOSE:

To determine the test-retest variability in perimetric, optic disc, and macular thickness parameters in a cohort of treated patients with established glaucoma.

PATIENTS AND METHODS:

In this cohort study, the authors analyzed the imaging studies and visual field tests at the baseline and 6-month visits of 162 eyes of 162 participant in the Glaucoma Imaging Longitudinal Study (GILS). They assessed the difference, expressed as the standard error of measurement, of Humphrey field analyzer II (HFA) Swedish Interactive Threshold Algorithm fast, Heidelberg retinal tomograph (HRT) II, and retinal thickness analyzer (RTA) parameters between the two visits and assumed that this difference was due to measurement variability, not pathologic change. A statistically significant change was defined as twice the standard error of measurement.

RESULTS:

In this cohort of treated glaucoma patients, it was found that statistically significant changes were 3.2 dB for mean deviation (MD), 2.2 for pattern standard deviation (PSD), 0.12 for cup shape measure, 0.26 mm for rim area, and 32.8 microm and 31.8 microm for superior and inferior macular thickness, respectively. On the basis of these values, it was estimated that the number of potential progression events detectable in this cohort by the parameters of MD, PSD, cup shape measure, rim area, superior macular thickness, and inferior macular thickness was 7.5, 6.0, 2.3, 5.7, 3.1, and 3.4, respectively.

CONCLUSIONS:

The variability of the measurements of MD, PSD, and rim area, relative to the range of possible values, is less than the variability of cup shape measure or macular thickness measurements. Therefore, the former measurements may be more useful global measurements for assessing progressive glaucoma damage.

Reliability and factorial validity of Adolescent Time Inventory-Time Attitude (ATI-TA) Scores in Scottish and Northern Irish adolescents

The contemporary literature investigating the construct broadly known as time perspective is replete with methodological and conceptual concerns. These concerns focus on the reliability and factorial validity of measurement tools, and the sample-specific modification of scales. These issues continue to hamper the development of this potentially useful psychological construct. An emerging body of evidence has supported the six-factor structure of scores on the Adolescent Time Inventory-Time Attitudes Scale, as well as their reliability. The present study utilized data from the first wave of a longitudinal study in the United Kingdom to examine the reliability, validity, and cross-cultural invariance of the scale. Results showed that the hypothesized six-factor model provided the best fit for the data; all alpha and omega estimates were >. .70; scores on ATI-TA factors related meaningfully to self-efficacy scores; and the factor structure was invariant across both research sites. Results are discussed in the context of the extant temporal literature.