Development of real-time process control systems using formal techniques

A major application of computers has been to control physical processes in which the computer is embedded within some large physical process and is required to control concurrent physical processes. The main difficulty with these systems is their event-driven characteristics, which complicate their modelling and analysis. Although a number of researchers in the process system community have approached the problems of modelling and analysis of such systems, there is still a lack of standardised software development formalisms for the system (controller) development, particular at early stage of the system design cycle. This research forms part of a larger research programme which is concerned with the development of real-time process-control systems in which software is used to control concurrent physical processes. The general objective of the research in this thesis is to investigate the use of formal techniques in the analysis of such systems at their early stages of development, with a particular bias towards an application to high speed machinery. Specifically, the research aims to generate a standardised software development formalism for real-time process-control systems, particularly for software controller synthesis. In this research, a graphical modelling formalism called Sequential Function Chart (SFC), a variant of Grafcet, is examined. SFC, which is defined in the international standard IEC1131 as a graphical description language, has been used widely in industry and has achieved an acceptable level of maturity and acceptance. A comparative study between SFC and Petri nets is presented in this thesis. To overcome identified inaccuracies in the SFC, a formal definition of the firing rules for SFC is given. To provide a framework in which SFC models can be analysed formally, an extended time-related Petri net model for SFC is proposed and the transformation method is defined. The SFC notation lacks a systematic way of synthesising system models from the real world systems. Thus a standardised approach to the development of real-time process control systems is required such that the system (software) functional requirements can be identified, captured, analysed. A rule-based approach and a method called system behaviour driven method (SBDM) are proposed as a development formalism for real-time process-control systems.

Deep hole drilling with twist drills: aspects of the CNC process and its real time monitoring and adaptive control

Deep hole drilling is one of the most complicated metal cutting processes and one of the most difficult to perform on CNC machine-tools or machining centres under conditions of limited manpower or unmanned operation. This research work investigates aspects of the deep hole drilling process with small diameter twist drills and presents a prototype system for real time process monitoring and adaptive control; two main research objectives are fulfilled in particular : First objective is the experimental investigation of the mechanics of the deep hole drilling process, using twist drills without internal coolant supply, in the range of diarneters Ø 2.4 to Ø4.5 mm and working length up to 40 diameters. The definition of the problems associated with the low strength of these tools and the study of mechanisms of catastrophic failure which manifest themselves well before and along with the classic mechanism of tool wear. The relationships between drilling thrust and torque with the depth of penetration and the various machining conditions are also investigated and the experimental evidence suggests that the process is inherently unstable at depths beyond a few diameters. Second objective is the design and implementation of a system for intelligent CNC deep hole drilling, the main task of which is to ensure integrity of the process and the safety of the tool and the workpiece. This task is achieved by means of interfacing the CNC system of the machine tool to an external computer which performs the following functions: On-line monitoring of the drilling thrust and torque, adaptive control of feed rate, spindle speed and tool penetration (Z-axis), indirect monitoring of tool wear by pattern recognition of variations of the drilling thrust with cumulative cutting time and drilled depth, operation as a data base for tools and workpieces and finally issuing of alarms and diagnostic messages.

A novel near real-time quality-control procedure for radiometric profiles measured by Bio-Argo floats: protocols and performances

An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called Case 1 waters. Around solar noon and almost everyday, each float acquires 0-250 m vertical profiles of Photosynthetically Available Radiation and downward irradiance at three wavelengths (380, 412 and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of operator’s control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. Here, we present a data quality-control procedure aimed at verifying profile shapes and providing near real-time data distribution. This procedure is specifically developed to: 1) identify main issues of measurements (i.e. dark signal, atmospheric clouds, spikes and wave-focusing occurrences); 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.

A novel near real-time quality-control procedure for radiometric profiles measured by Bio-Argo floats: protocols and performances

An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called Case 1 waters. Around solar noon and almost everyday, each float acquires 0-250 m vertical profiles of Photosynthetically Available Radiation and downward irradiance at three wavelengths (380, 412 and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of operator’s control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. Here, we present a data quality-control procedure aimed at verifying profile shapes and providing near real-time data distribution. This procedure is specifically developed to: 1) identify main issues of measurements (i.e. dark signal, atmospheric clouds, spikes and wave-focusing occurrences); 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.

Real-time PCR demonstrates high prevalence of Schistosoma japonicum in the Philippines:implications for surveillance and control

BACKGROUND: The Philippines has a population of approximately 103 million people, of which 6.7 million live in schistosomiasis-endemic areas with 1.8 million people being at risk of infection with Schistosoma japonicum. Although the country-wide prevalence of schistosomiasis japonica in the Philippines is relatively low, the prevalence of schistosomiasis can be high, approaching 65% in some endemic areas. Of the currently available microscopy-based diagnostic techniques for detecting schistosome infections in the Philippines and elsewhere, most exhibit varying diagnostic performances, with the Kato-Katz (KK) method having particularly poor sensitivity for detecting low intensity infections. This suggests that the actual prevalence of schistosomiasis japonica may be much higher than previous reports have indicated.

METHODOLOGY/PRINCIPAL FINDINGS: Six barangay (villages) were selected to determine the prevalence of S. japonicum in humans in the municipality of Palapag, Northern Samar. Fecal samples were collected from 560 humans and examined by the KK method and a validated real-time PCR (qPCR) assay. A high S. japonicum prevalence (90.2%) was revealed using qPCR whereas the KK method indicated a lower prevalence (22.9%). The geometric mean eggs per gram (GMEPG) determined by the qPCR was 36.5 and 11.5 by the KK. These results, particularly those obtained by the qPCR, indicate that the prevalence of schistosomiasis in this region of the Philippines is much higher than historically reported.

CONCLUSIONS/SIGNIFICANCE: Despite being more expensive, qPCR can complement the KK procedure, particularly for surveillance and monitoring of areas where extensive schistosomiasis control has led to low prevalence and intensity infections and where schistosomiasis elimination is on the horizon, as for example in southern China.

Recommendations for in-situ data Near Real Time Quality Control

With the construction of operational oceanography systems, the need for real-time has become more and more important. A lot of work had been done in the past, within National Data Centres (NODC) and International Oceanographic Data and Information Exchange (IODE) to standardise delayed mode quality control procedures. Concerning such quality control procedures applicable in real-time (within hours to a maximum of a week from acquisition), which means automatically, some recommendations were set up for physical parameters but mainly within projects without consolidation with other initiatives. During the past ten years the EuroGOOS community has been working on such procedures within international programs such as Argo, OceanSites or GOSUD, or within EC projects such as Mersea, MFSTEP, FerryBox, ECOOP, and MyOcean. In collaboration with the FP7 SeaDataNet project that is standardizing the delayed mode quality control procedures in NODCs, and MyOcean GMES FP7 project that is standardizing near real time quality control procedures for operational oceanography purposes, the DATA-MEQ working group decided to put together this document to summarize the recommendations for near real-time QC procedures that they judged mature enough to be advertised and recommended to EuroGOOS.

Copernicus In Situ TAC, Real Time Quality Control for WAVES

In April 2017, CMEMS plans to launch the WAVES NRT products. This document is focused in the automatic RTQC of the collected wave data. The validation procedure includes the delayed mode quality control of the data and will be specified in another guideline. To perform any kind of quality control to wave data, first it’s necessary to know the nature of the measurements and the analysis performed to those measurements to obtain the wave parameters. For that reason next chapter is dedicated to show the usual wave analysis and the different parameters and estimators obtained.

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.