An LMI based Robust H? SOF Controller for AVR in an SMIB System

This paper presents the design of an H? (H-infinity) controller to stabilize an uncertain power system using mixed sensitivity approach through an iterative LMI (Linear Matrix Inequality) algorithm. Here a robust control methodology is suggested to improve the voltage regulation of a synchronous generator. H? control method is used in this control theory to synthesize controller to obtain robust performance and stabilization. This technique has the advantage over classical control techniques that it is readily applicable to the problems including multivariable systems. The proposed robust controller enhances the performance as well as minimizes the disturbances’ effect more effectively. In this paper the controller is designed and simulated under MATLAB/Simulink for electric generator stabilization studies for an SMIB system

Structuring Guidelines for Web Application Designers - A Meta-model

International audienc

Signal Processing Combined with Machine Learning for Biomedical Applications

The Master’s thesis is comprised of four projects in the realm of machine learning and signal processing. The abstract of the thesis is divided into four parts and presented as follows, Abstract 1: A Kullback-Leibler Divergence-Based Predictor for Inter-Subject Associative BCI. Inherent inter-subject variability in sensorimotor brain dynamics hinders the transferability of brain-computer interface (BCI) model parameters across subjects. An individual training session is essential for effective BCI control to compensate for variability. We report a Kullback-Leibler Divergence (KLD)-based predictor for inter-subject associative BCI. An online dataset comprising left/right hand, both feet, and tongue motor imagery tasks was used to show correlation between the proposed inter-subject predictor and BCI performance. Linear regression between the KLD predictor and BCI performance showed a strong inverse correlation (r = -0.62). The KLD predictor can act as an indicator for generalized inter-subject associative BCI designs. Abstract 2: Multiclass Sensorimotor BCI Based on Simultaneous EEG and fNIRS. Hybrid BCI (hBCI) utilizes multiple data modalities to acquire brain signals during motor execution (ME) tasks. Studies have shown significant enhancements in the classification of binary class ME-hBCIs; however, four-class ME-hBCI classification is yet to be done using multiclass algorithms. We present a quad-class classification of ME-hBCI tasks from simultaneous EEG-fNIRS recordings. Appropriate features were extracted from EEG-fNIRS signals and combined for hybrid features and classified with support vector machine. Results showed a significant increase in hybrid accuracy over single modalities and show hybrid method’s performance enhancement capability. Abstract 3: Deep Learning for Improved Inter-Subject EEG-fNIRS Hybrid BCI Performance. Multimodality based hybrid BCI has become famous for performance improvement; however, the inherent inter-subject and inter-session variation between participants brain dynamics poses obstacles in achieving high performance. This work presents an inter-subject hBCI to classify right/left-hand MI tasks from simultaneous EEG-fNIRS recordings of 29 healthy subjects. State-of-art features were extracted from EEG-fNIRS signals and combined for hybrid features, and finally, classified using deep Long short-term memory classifier. Results showed an increase in the inter-subject performance for the hybrid system while making the system more robust to brain dynamics change and hints to the feasibility of EEG-fNIRS based inter-subject hBCI. Abstract 4: Microwave Based Glucose Concentration Classification by Machine Learning. Non-invasive blood sugar measurement attracts increased attention in recent years, given the increase in diabetes-related complications and inconvenience in the traditional ways using blood. This work utilized machine learning (ML) algorithms to classify glucose concentration (GC) from the measured broadband microwave scattering signals (S11). An N-type microwave adapter pair was utilized to measure the sweeping frequency scattering-parameter (S-parameter) of the glucose solutions with GC varying from 50-10,000 dg/dL. Dielectric parameters were retrieved from the measured wideband complex S-parameters based on the modified Debye dielectric dispersion model. Results indicate that the best algorithm can achieve a perfect classification accuracy and suggests an alternate way to develop a GC detection method using ML algorithms

Mathematical Model of Plant Leaf Area Growth

In this paper, we introduce a mathematical model of plant growth, from the seedling to shipping of the adult plant. Our model has three parts. The first analyzes plant growth, the second models the fertilizer supply system, and the third identifies an optimal control strategy by matching the control system to the growth density. The mathematical model was defined using bilinear partial differential equations, but these were replaced by a strictly linear model

PROFIT AND LOSS ANALYSIS ON A PRODUCTION BUSINESS USING LEADTIME FUNCTION

We propose a profit and loss analysis on the outlet side of a production flow processes using a lead time function. This is the ongoing study, which analyzes a production process by using a lead time function. With respect to a production business, we need to secure operating revenue as a production company. To analyze the profit and loss on a production business, we introduce a system for the evaluation of revenue under the conditions of borrowing and capital repayments. We use the actual data obtained from a production flow process for evaluation of the break even point. With regard to a value after a repayment, whether the value is changed or not in the case where a guaranty by a company president is required is reported. In addition, how a value of manufacturing equipment (remaining value) changes after a repayment of a loan relative to a repayment period is reported. Finally, a degree (sensitivity) of influence of parameters, an initial plan money amount, a repaid money amount and a repayment period, on a remaining value and a result of risk analysis is also reported

Rotary Light Emitting Diode Display with RGB System

Abstrak LED screen adalah pengembangan dari penggunaan LED untuk menampilkan informasi. Alternatif dari LED screen sebagai media tampilan adalah rotary LED display. Teknologi rotary merupakan metode baru dalam menampilkan informasi dengan menggunakan media LED. Teknik ini memanfaatkan pembagian ruang dalam segmen-segmen kemudian LED dinyalakan secara multipleks. Hal ini dimungkinkan dengan memanfaatkan persistence of vision dari mata manusia. Hasil kualitatif dari alat “Rotary LED Display dengan Sistem RGB†menunjukkan bahwa informasi berupa karakter alfanumerik dapat ditangkap mata dalam warna merah, biru, dan hijau. Informasi yang ditampilkan LED screen dapat ditampilkan juga dalam sistem LED rotary. Keunggulan tampilan dengan teknik rotary dibanding LED screen adalah penggunaan hardware LED yang lebih sedikit untuk menampilkan informasi dengan resolusi yang sama. Berkurangnya penggunaan LED menyebabkan daya yang digunakan rotary LED lebih sedikit dibandingkan LED screen. Kata kunci: Rotary LED, RGB,Persistance of Vision Abstract LED screen is the development of LED application as a source of information. An alternative to utilize LED as a medium of information is rotary LED display. Rotary technology is a novelty method in information display by using LED as foundation. The technique is by separating space in segments and then flicking LED in multiplexing sequence. This is made possible by utilizing human eyes’ persistence of vision. The qualitative result of the “Rotary LED Display with RGB System†shows that the information in the form of alphanumeric character can be seen by human eyes in red, blue, and green colors. The same information seen in LED screen can also be shown in rotary LED system. The advantage of rotary LED display is the reduced LED usage for the same resolution result. The decreased use of LED resulted in the reduced power consumption compared to the LED screen. Keywords: Rotary LED, RGB,Persistance of Visio

Optimal Servo Design for distributed parameter system defined by a bilinear partial differential equation

We propose a mathematical model described in a bilinear partial differential equation of nonlinear coupled with state variable and control variable in this study. Furthermore, we propose the optimal servo system design of the stochastic model considering the disturbance. The general mixing reaction system is described in a bilinear partial differential equation.The complete mixing reaction system is assumed to maintain a space uniformly, we construct a bilinear model lumped parameter system. The target model is linearized by using a exact linear theory, we present a design proposal on the optimal servo system considering a disturbance into the system

A dynamic span model and associated control strategy for roll-transport systems used for sheet materials (Part II)

In this study, we propose a mathematical model that simulates the tension occurring at stands between rolls in a roll-transport system, and then we propose a method to estimate tension. The model is a lumped parameter system described by an ordinary differential equation (ODE). The ODE is derived on the basis of the tension of the stages between drive rolls on the stands. To build a realistic system, we utilized an estimation theory, which is the Kalman filter theory in a control theory. As a result, the proposed system is highly feasible

AN OPTIMAL PRODUCTION CAPACITY CONTROL INCLUDING OUTSIDE SUPPLIERS

This study is part of an ongoing report on an analysis of production processes using a lead-time function. We present a strategy for determining the optimal production capacity using a quadratic form evaluation function in the production process. A mathematical model of production process is introduced by a stochastic differential equations with a lognormal type. In general, a production capacity is proportional to the rate of return. To determine the optimal production capacity, we calculated the optimal solution by introducing the Hamilton-Jacobi-Bellman equation. We determine the optimum parameters of the quadratic form evaluation function on the basis of the optimal capacity solution. We reported that an optimal production capacity is highly dependent on a volatility in workers. Further, we present the actual throughput data for a production flow process with high productivity (using a synchronous method) and in the absence of a production flow process (using an asynchronous method). The production efficiency of the synchronous process becomes clear from the actual data. For further verification, we confirmed the benefit of using the synchronization process to attempt to perform dynamic simulation