Root cause isolation of propagated oscillations in process plants

Persistent whole-plant disturbances can have an especially large impact on product quality and running costs. There is thus a motivation for the automated detection of a plant-wide disturbance and for the isolation of its sources. Oscillations increase variability and can prevent a plant from operating close to optimal constraints. They can also camouflage other behaviour that may need attention such as upsets due to external disturbances. A large petrochemical plant may have a 1000 or more control loops and indicators, so a key requirement of an industrial control engineer is for an automated means to detect and isolate the root cause of these oscillations so that maintenance effort can be directed efficiently. The propagation model that is proposed is represented by a log-ratio plot, which is shown to be ‘bell’ shaped in most industrial situations. Theoretical and practical issues are addressed to derive guidelines for determining the cut-off frequencies of the ‘bell’ from data sets requiring little knowledge of the plant schematic and controller settings. The alternative method for isolation is based on the bispectrum and makes explicit use of this model representation. A comparison is then made with other techniques. These techniques include nonlinear time series analysis tools like Correlation dimension and maximal Lyapunov Exponent and a new interpretation of the Spectral ICA method, which is proposed to accommodate our revised understanding of harmonic propagation. Both simulated and real plant data are used to test the proposed approaches. Results demonstrate and compare their ability to detect and isolate the root cause of whole plant oscillations. Being based on higher order statistics (HOS), the bispectrum also provides a means to detect nonlinearity when oscillatory measurement records exist in process systems. Its comparison with previous HOS based nonlinearity detection method is made and the bispectrum-based is preferred

Controllers, observers, and applications thereof

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed

Finding the source of nonlinearity in a process with plant-wide oscillation

Published versio

Scan Test Coverage Improvement Via Automatic Test Pattern Generation (Atpg) Tool Configuration

The scan test coverage improvement by using automatic test pattern generation (ATPG) tool configuration was investigated. Improving the test coverage is essential in detecting manufacturing defects in semiconductor industry so that high quality products can be supplied to consumers. The ATPG tool used was Mentor Graphics Tessent TestKompress (version 2014.1). The study was done by setting up a few experiments of utilizing and modifying ATPG commands and switches, observing the test coverage improvement from the statistical reports provided during pattern generation process and providing relatable discussions. By modifying the ATPG commands, it can be expected to have some improvement in the test coverage. The scan test patterns generated were stuck-at test patterns. Based on the experiments done, comparison was made on the different coverage readings and the most optimized method and flow of ATPG were determined. The most optimized flow gave an improvement of 0.91% in test coverage which is acceptable since this method does not involve a change in design. The test patterns generated were converted and tested using automatic test equipment (ATE) to observe its performance on real silicon. The test coverage improvement using ATPG tool instead of the design-based method is important as a faster workaround for back-end engineers to provide high quality test contents in such a short product development duration

Remote maintenance of control system performance over the internet

The Internet provides a significant benefit for the remote maintenance and fault diagnosis of various devices and plants. One such example is the UK’s distributed aircraft maintenance environment (DAME) (www.cs.york.ac.uk/dame), which provides a genetic test bed for distributed diagnostics based on Grid-enabled technologies. This paper focuses on developing a systematic method for the design of such a remote maintenance systems specifically for process control systems. Design issues of Internet-based remote maintenance systems for process control such as that proposed here include control performance assessment, fault detection, control performance maintenance, and heterogeneous data transfer over the Internet. A back-end and front-end architecture is proposed, in which all the heavy calculations are carried out locally. Light data and the characteristics of any heavy data are sent to the front-end located on the remote server for consideration by remote experts. The remote maintenance system is illustrated by reference to the implementation in a process control rig

Benchmarking of Advanced Control Strategies for a Simulated Hydroelectric System

This paper analyses and develops the design of advanced control strategies for a typical hydroelectric plant during unsteady conditions, performed in the Matlab and Simulink environments. The hydraulic system consists of a high water head and a long penstock with upstream and downstream surge tanks, and is equipped with a Francis turbine. The nonlinear characteristics of hydraulic turbine and the inelastic water hammer effects were considered to calculate and simulate the hydraulic transients. With reference to the control solutions addressed in this work, the proposed methodologies rely on data-driven and model-based approaches applied to the system under monitoring. Extensive simulations and comparisons serve to determine the best solution for the development of the most effective, robust and reliable control tool when applied to the considered hydraulic system

Measurements, Models, Systems and Design

531 s.