Hardware-in-the-loop simulation of DC motor as an instructional media for control system design and testing

Instructional media in control systems typically requires a real plant as an element to be controlled. However, this real plant, which is costly to be implemented, can be replaced by a virtual plant implemented in a computer and modelled in such a way that it resembles the behavior of a real plant. This kind of set-up is widely termed as hardware-in-the-loop (HIL) simulation. HIL simulation is an alternative way to reduce the development cost. A virtual plant is easy to adjust to represent various plants or processes that are widely used in industry. This paper proposes a simple HIL simulation set-up designed as instructional media for design and testing a simple control system. The experimental result on DC motor control shows that HIL simulation dynamical response is similar to the real hardware response with a small average error on measured transient response, represented in 0.5 seconds difference in settling time and 7.43 % difference in overshoot. This result shows the efficacy of our HIL simulation set-up.

L-system models for image-based phenomics: case studies of maize and canola

Artificial neural networks that recognize and quantify relevant aspects of crop plants show great promise in image-based phenomics, but their training requires many annotated images. The acquisition of these images is comparatively simple, but their manual annotation is time-consuming. Realistic plant models, which can be annotated automatically, thus present an attractive alternative to real plant images for training purposes. Here we show how such models can be constructed and calibrated quickly, using maize and canola as case studies.

Phyllotaxis Models: from the Inhibition Potential to the Real Plant

Previous phyllotaxis models allowed the initiation of new primordia when a threshold of inhibition potential is reached on the meristem front: their adequacy to botanical reality is only qualitative. We formulated the hypothesis that it is not the value of the inhibition threshold that remains constant as the meristem develops, but the difference of the inhibition thresholds during the initiation of two successive primordia. We were thus able to model with accuracy the sequence of plastochron ratios observed by Williams (1975) on the leaf meristem of flax: an outstanding result. More generally, we have shown that the evolution trajectories of the phyllotaxis modes as a function of the plastochron ratios follow the minima of the potential under decreasing plastochron ratios constraint and bifurcate when the number of these minima increases, thus giving physicochemical foundations to the famous van Iterson diagram. This historical representation of rising phyllotaxis shows the trajectories, but doesnt give the velocity of the movement: our plastochron ratio sequence adds this major dynamical information.

A Multivariate Heterogeneous Variance Components Model for Multi-Environment Studies with Locational Genetic Effects

In this paper a multivariate heterogeneous variance components model is developed, which allows for determining location specific variance components in the analysis of multiple related traits. In addition to spatial heterogeneity, genetic similarities are also considered by assigning genetic variance components. The performance of the developed model is evaluated through an extensive simulation study and comparison of models are conducted by heritability estimations. Simulation study reveals that the developed method can well control the locational heterogeneity and under the developed model the heritability estimations are close to desired proportions. A real plant breeding data set is used for illustration.

Development and validation of a robust integrated thermal power plant model for load loss analysis and identification

The development of deep learning methodologies for the analysis of thermal power plant load losses requires a combination of real plant data and data derived from fundamental physics-based process models. For this purpose, a robust integrated power plant thermofluid process model of a complete +600MW coal-fired power plant was developed within the Flownex Simulation Environment. It consists of standard and compound components, combined with specially developed scripts to ensure complete energy balance, specifically on the two-phase tank components. This enables simulation of the complete plant operation to determine power output as a function of any given set of internal and external operational variables, boundary conditions and component states. The model was validated against real plant design and acceptance test data. In order to demonstrate the ability of the model it was used to evaluate the plant performance related to three specific load loss inducing scenarios. The results show that a combination of mechanical faults, process anomalies and operational phenomena can be analysed. This provides the basis for generating model-based performance data that can be combined with real plant data to facilitate the development of deep learning analytics tools for load loss fault diagnosis and root cause analysis, as well as fault propagation and load loss forecasting.

NEUTRON NOISE SPECTRAL FEATURES OF SIMULATED MECHANICAL AND THERMAL-HYDRAULIC PERTURBATIONS IN A PWR CORE

KWU-PWR reactors (SIEMENS design) are commonly exhibiting high neutron noise levels that can lead to costly operational issues. Recent analysis seems to indicate that, coolant flow, temperature oscillations, and mechanical vibrations have a key impact on neutron noise phenomena. In order to advance in understanding this phenomenon, the transient nodal code SIMULATE-3K (S3K) has been already utilized to simulate scenarios with individual or combined types of perturbation sources: mechanical vibrations of fuel assemblies and thermal-hydraulic fluctuations at the core inlet. In this work, new simulations are performed with all the perturbations applied simultaneously. The simulated neutron detectors responses are then analyzed with noise analysis techniques. All the simulated spectral features of neutron noise are compared to those obtained from real plant data. Results show that the simulated neutron noise phenomenology behaves similarly to that obtained from real plant data by increasing the fluctuation amplitude in the inlet coolant flow in the S3K calculations.

TRIGA PUSPATI reactor: model analysis and accuracy

<p>There are many challenging issues with research reactor, such as time variation and uncertainty. Since its first criticality in 1982, the biggest changes in TRIGA PUSPATI Reactor system is the replacement of instrumentation and control console system from analogue to digital in 2013. Apart from providing methods of controlling the power reactor via the control rod movement, the Instrumentation and Control Console System also provides monitoring and display for all reactor parameters to protect the reactor from undue influences or abnormal circumstances. Meanwhile, the simulation model of the TRIGA PUSPATI Reactor system has been developed in the Simulink-MATLAB. The simulation model development is based on the research reactor mathematical representatives and the real plant parameters of TRIGA PUSPATI Reactor. However, the performance of this simulation model needs to be evaluated. Since there is no report or paper work found on the performance of the simulation model to represent the real system of RTP, the present study aims to carry out an analysis for more rigorous understanding of the TRIGA PUSPATI Reactor model simulation through validation and verification methods. After analysing the result, it was found that the simulation model has a good representation of a real plant.</p>

Improving model-based compensation method for real-time hybrid simulation considering error of identified model

Time delay is a critical and unavoidable problem in real-time hybrid simulation. An accurate and effective compensation method for time delay is necessary for the safety of real-time hybrid simulation and the reliability of test results. Generally, a model-based compensation method can be adopted, which is derived from the identified transfer function by assuming the latter can accurately represent the real plant. However, there must be some differences between the transfer function and the real plant. To facilitate the development of real-time hybrid simulation, we proposed a two-stage feedforward compensation method considering the error between the transfer function identified and the real plant. The compensation strategy proposed in this study was not only based on the transfer function but also introduced an error model as a second-stage compensation into a compensator to realize the synchronization of command and measurement. To verify the efficiency of the proposed method, comparisons in time domain and frequency domain with the feedforward compensator in a model-based feedforward–feedback control method were carried out. Compared with the feedforward compensator, the two-stage method achieved better tracking performance, especially in the high-frequency bandwidth. The test results verified that for a band-limited white noise of 0–30 Hz, the phase lag of the actuation system can be limited to ±5°. Finally, the two-stage method was applied to a real-time hybrid simulation of a two-story frame to illustrate its compensation effect on time delay.