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1

Probabilistic lane segmentation using a low-dimensional linear parametrization

Acuña Carlos, Arechavaleta Gustavo, Castelán Mario

International Journal of Applied Mathematics and Computer Science

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2025

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Vol. 35, no. 1

179--189

EN

Lane detection is an important module for active safety systems since it increases safety and reduces traffic accidents caused by driver inattention. Illumination changes or occlusions make lane detection a challenging task, especially if the detection is performed from a single image. Consequently, this paper presents a probabilistic approach based on the Kalman filter, which uses information from previous image frames to estimate the lane that could not be detected in the current image frame, considering uncertainty in the prediction as well as in the detection. To this end, a principal component analysis of the segmented curvature is introduced with the purpose of dimensionality reduction, moving from a large dimensional pixel representation to a considerably reduced space representation. Furthermore, the proposed approach is compared with a fully connected pretrained CNN model for lane detection, demonstrating that the proposed method has a lower computational cost in addition to a smoother transition between lane estimates.

2

Filtr Kalmana jako alternatywa dla rozszerzonego obserwatora stanu w algorytmie regulacji ADRC

Michalski Jacek, Mrotek Mikołaj, Kozierski Piotr

Pomiary Automatyka Robotyka

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2024

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R. 28, nr 1

31--39

PL

W artykule przedstawiono zmodyfikowany algorytm odpornej regulacji z aktywną kompensacją zaburzeń ADRC z wykorzystaniem filtru Kalmana KF do estymacji rozszerzonego wektora stanu. Filtrem Kalmana zastąpiono używany w podstawowej formie rozszerzony obserwator stanu ESO. Modyfikacja ta pozwoliła na poprawę odporności układu w warunkach działania pomiarowych zakłóceń stochastycznych. Przedstawiono sposób syntezy układu regulacji i doboru nastaw filtru Kalmana zapewniający skuteczność sterowania, a także pokazano ich wpływ na działanie układu. Eksperymenty zostały przeprowadzone na układzie laboratoryjnym z balansującą na stole kulą BBT. Jakość regulacji została oceniona na podstawie przebiegów czasowych oraz całkowych wskaźników jakości, dla różnych konfiguracji nastaw oraz poziomów zaszumienia. W wyniku badań wykazana została przewaga zastosowania filtru Kalmana nad obserwatorem pod kątem wrażliwości na szumy pomiarowe. Zastosowanie filtru Kalmana jako estymatora dla rozszerzonego stanu wykazało pozytywny wpływ na jakość regulacji i zdolność do odrzucania zakłóceń wewnętrznych również w układzie deterministycznym.

EN

The article presents a modified Active Disturbance Rejection Control (ADRC) algorithm that uses the Kalman Filter (KF) for the estimation of extended state vector. The Kalman filter replaced the Extended State Observer (ESO) used in its basic form. The purpose of this modification was to improve the system robustness under conditions of stochastic measurement disturbances. The method of the control system synthesis and the Kalman filter gains selection, ensuring control efficiency, as well as their impact on the system operation, were presented. The experiments were carried out on a laboratory setup - the Ball Balancing Table (BBT). Control quality was assessed based on time plots of signals and integral performance indices for various algorithm gains configurations and different noise levels. As a result of the conducted research, the advantage of using the Kalman filter over the ESO in terms of sensitivity to measurement noises was demonstrated. Implementation of the Kalman filter as the ESO determined a positive impact on control quality and the ability to reject internal disturbance also in a deterministic system.

3

Degradation tolerant optimal control design for stochastic linear systems

Kanso Soha, Jha Mayank Shekhar, Theilliol Didier

International Journal of Applied Mathematics and Computer Science

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2024

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Vol. 34, no. 1

5--14

EN

Safety-critical and mission-critical systems are often sensitive to functional degradation at the system or component level. Such degradation dynamics are often dependent on system usage (or control input), and may lead to significant losses and a potential system failure. Therefore, it becomes imperative to develop control designs that are able to ensure system stability and performance whilst mitigating the effects of incipient degradation by modulating the control input appropriately. In this context, this paper proposes a novel approach based on an optimal control theory framework wherein the degradation state of the system is considered in the augmented system model and estimated using sensor measurements. Further, it is incorporated within the optimal control paradigm leading to a control law that results in deceleration of the degradation rate at the cost of system performance whilst ensuring system stability. To that end, the speed of degradation and the state of the system in discrete time are considered to develop a linear quadratic tracker (LQT) and regulator (LQR) over a finite horizon in a mathematically rigorous manner. Simulation studies are performed to assess the proposed approach.

4

Hydrological Forecasts Modeling Using Artificial Intelligence and Conceptual Models of KébirRhumel Watershed, Algeria

Ramzi Khaldi, Nadir Marouf, Tewfik Bouziane Mohamed, Hakim Djafer Khodja

Ecological Engineering & Environmental Technology

|

2024

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Vol. 25, iss. 9

68--80

EN

This study models the rainfall-runoff relationship in the Kebir-Rhumel River watershed in the Constantine Highlands, Algeria, using data from three concomitant rainfall and hydrometric stations. Statistical tests confirmed the absence of breaks in the series. We applied four conceptual models (GR4J, IHAC6, MORDOR, TOPMO8) and neural network models (RNN, NARX, LSTM) over three- and ten-year periods. Among the conceptual models, GR4J provided the best fit, highlighting the non-stationary nature of the relationship. The PMC neural network model performed well over three years but was less effective over ten years due to low flow influence. Notably, the NARX-RNN and RNN-LSTM models showed excellent predictive accuracy, with NARX-RNN perfectlycapturing flow dynamics and RNN-LSTM achieving minimal RMSE and high correlation coefficients. This study lies the comparative analysis of conceptual and neural network models, specifically the NARX-RNN and RNN-LSTM models, which have not been extensively applied in this context. This research fills the gap in understanding the effectiveness of neural network models in modelling non-stationary rainfall-runoff relationships in the region.

5

Selected applications of satellite technologies in rail transport

Chrzan Marcin, Ciszewski Tomasz, Nowakowski Waldemar

Archives of Transport

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2024

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Vol. 71, iss. 3

91--105

EN

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity requirements, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative documents. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the authors, the described methods can also be used in many other tasks related to rail transport.

6

Monitorowanie drgań mechanicznych elektrowni wiatrowych o pionowej osi obrotu

Ciura Krzysztof, Jąderko Andrzej, Rakowska Luiza

Przegląd Elektrotechniczny

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2023

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R. 99, nr 12

280--283

PL

W artykule pokazano system służący do monitorowania drgań mechanicznych pochodzących od elektrowni wiatrowych o pionowej osi obrotu, które mieszczą się na dachu budynku F Wydziału Elektrycznego Politechniki Częstochowskiej. Do wyznaczenia charakteru drgań mechanicznych wykorzystano czujniki drgań wraz z obsługującym je mikrokontrolerem ARDIUNO zamontowane na konstrukcjach nośnych turbin wiatrowych na budynku. Oprogramowanie systemu wykonano w środowisku programistycznym C++. Do filtracji sygnałów z czujników drgań zastosowano rekursywny Filtr Kalmana. Opracowane oprogramowanie umożliwia wizualizację, analizę i archiwizację danych pomiarowych.

EN

The article presents a system for monitoring mechanical vibrations from wind turbines with a vertical axis of rotation, which are located on the roof of the building F of the Faculty of Electrical Engineering of the Czestochowa University of Technology. To determine the nature of mechanical vibrations, vibration sensors were used along with the ARDIUNO microcontroller, mounted on the supporting structures of the wind turbines in the building. The system software was developed in the C++ development environment. A recursive Kalman Filter was used to filter signals from vibration sensors. The developed software enables the visualization, analysis and archiving of measurement data.

7

Comparison of the effectiveness of time series analysis methods: SMA, WMA, EMA, EWMA, and Kalman filter for data analysis

Lotysh Volodymyr, Gumeniuk Larysa, Humeniuk Pavlo

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2023

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T. 13, nr 3

71--74

EN

In time series analysis, signal processing, and financial analysis, simple moving average (SMA), weighted moving average (WMA), exponential moving average (EMA), exponential weighted moving average (EWMA), and Kalman filter are widely used methods. Each method has its own strengths and weaknesses, and the choice of method depends on the specific application and data characteristics. It is important for researchers and practitionersto understand the properties and limitations of these methods in order to make informed decisions when analyzing time seriesdata. This study investigates the effectiveness of time series analysis methods using data modeled with a known exponential function with overlaid random noise. This approach allows for control of the underlying trend in the data while introducing the variability characteristic of real-world data. The relationships were written using scripts for the construction of dependencies, and graphical interpretation of the results is provided.

PL

W analizie szeregów czasowych, przetwarzaniu sygnałów i analizie finansowej szeroko stosowane są: prosta średnia ruchoma (SMA), ważona średnia ruchoma (WMA), wykładnicza średniaruchoma (EMA), wykładniczo-ważona średnia ruchoma (EWMA) i filtr Kalmana. Każda z metod ma swoje mocne i słabe strony, a wybór metody zależy od konkretnego zastosowania i charakterystyki danych. Dla badaczyi praktyków ważne jest zrozumienie właściwości i ograniczeń tych metod w celu podejmowania świadomych decyzji podczas analizy danych szeregów czasowych. W niniejszej pracy zbadano skuteczność metod analizy szeregów czasowych z wykorzystaniem danych modelowanych znaną funkcją wykładniczą z nałożonym szumem losowym. Takie podejście pozwala na kontrolowanie głównego trendu w danych przy jednoczesnym wprowadzeniu zmienności typowej dla danych rzeczywistych. Do budowy zależności zostały napisane skrypty. Podanajest graficzna interpretacja wyników.

8

Fault diagnosis-based observers using Kalman filters and Luenberger estimators: Application to the pitch system fault actuators

Zemali Zakaria, Cherroun Lakhmissi, Hadroug Nadji, Nadour Mohamed, Hafaifa Ahmed

Diagnostyka

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2023

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Vol. 24, No. 1

art. no. 2022110

EN

This paper aims to present a robust fault diagnosis structure-based observers for actuator faults in the pitch part system of the wind turbine benchmark. In this work, two linear estimators have been proposed and investigated: the Kalman filter and the Luenberger estimator for observing the output states of the pitch system in order to generate the appropriate residual between the measured positions of blades and the estimated values. An inference step as a decision block is employed to decide the existence of faults in the process, and to classify the detected faults using a predetermined threshold defined by upper and lower limits. All actuator faults in the pitch system of the horizontal wind turbine benchmark are studied and investigated. The obtained simulation results show the ability of the proposed diagnosis system to determine effectively the occurred faults in the pitch system. Estimation of the output variables is effectively realized in both situations: without and with the occurrence of faults in the studied process. A comparison between the two used observers is demonstrated.

9

Application of fuzzy type II multi-layer Kalman filter for parameters identification of two-mass drive system

Śleszycki Kacper, Wróbel Karol, Szabat Krzysztof, Katsura Seiichiro

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 4

art. no. e146107

EN

The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests.

10

Thermodynamics-based measurement of the velocity of high-temperature smoke

Wang Haoyu

Archives of Thermodynamics

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2023

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Vol. 44, no. 1

23--36

EN

In view of the high cost and difficulty of ensuring the accuracy in the measurement of fire smoke velocity, the measurement system developed using platinum resistance temperature detectors and an 8-bit microcontroller, is used to realize the fast measurement of high-temperature fire smoke velocity. The system is based on the thermodynamic method and adopts the Kalman filter algorithm to process the measurement data, so as to eliminate noise and interference, and reduce measurement error. The experimental results show that the Kalman filter algorithm can effectively improve the measurement accuracy of fire smoke velocity. It is also shown that the system has high measurement accuracy, short reaction time, low cost, and is characterized by high performance in the measurement of high-temperature smoke velocity in experiments and practice.

11

Mechatroniczny projekt dwukołowej platformy mobilnej

Ręczkowicz Szymon

Mining – Informatics, Automation and Electrical Engineering

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2022

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R. 60, nr 2

35--52

PL

W artykule przedstawiono wyniki prac nad projektem dwukołowej samobalansującej platformy mobilnej przygotowanym w ramach pracy inżynierskiej. Celem stworzenia konstrukcji było umożliwienie zwiększania mobilności osoby dorosłej na niewielkich odległościach w zurbanizowanym środowisku. Całość prac projektowych podzielono na kilka części. W pierwszym etapie przedstawiono wymagania założone dla projektu urządzenia, dobrano elementy elektryczne oraz schemat ich połączeń elektrycznych. W drugiej części omówiono stworzony model CAD konstrukcji oraz jego elementy mechaniczne. W celu sprawdzenia wytrzymałości konstrukcji dokonano analizy MES korpusu urządzenia. Przedostatnią częścią było przeanalizowanie zagadnienia odwróconego wahadła, które pozwoliło na wyprowadzenie modelu przestrzeni stanu z rozdzieleniem na podsystemy bazy i drążka sterowniczego niezbędnego do opracowania sterowania dla platformy. W ostatniej części przygotowano algorytm stabilizujący na podstawie regulatora LQR oraz rozważano zastosowanie fuzji sensorycznej w postaci filtru Kalmana w celu zwiększenia dokładności określania kąta odchylenia konstrukcji. Na koniec przygotowano symulacje w środowisku Simulink w celu sprawdzenia poprawności przygotowanego algorytmu. Całość została zwieńczona podsumowaniem prac oraz wytyczeniem kierunków dalszych badań.

EN

The article presents the results of work on a project for a two-wheeled self-balancing mobile platform prepared as part of engineering work. The purpose of creating the structure was to enable the increased mobility of an adult over short distances in an urbanized environment. The whole design work was divided into several parts. In the first stage, requirements were assumed for the design of the device, electrical elements chosen, and a diagram of their electrical connections is presented. In the second part, the created CAD model of the structure is presented and some of mechanical elements described. In order to check the strength of the structure, the FEM analysis of the device body was carried out. The penultimate part was to analyze the problem of the inverted pendulum, which allowed to separate the state space model into a base subsystem and a control stick subsystem necessary to develop the control for the platform. In the last part, a stabilizing algorithm based on the LQR regulator was prepared and the use of sensory fusion in the form of a Kalman filter was focused on in order to increase the accuracy of determining the angle of deflection of the structure. Finally, simulations were prepared in the Simulink environment in order to check the correctness of the prepared algorithm. The whole was crowned with a summary of the work and setting directions for further research.

12

Mechatronic design of a two-wheeled mobile platform

Ręczkowicz Szymon

Mining – Informatics, Automation and Electrical Engineering

|

2022

|

R. 60, nr 2

17--34

EN

The article presents the results of work on a project for a two-wheeled self-balancing mobile platform prepared as part of engineering work. The purpose of creating the structure was to enable the increased mobility of an adult over short distances in an urbanized environment. The whole design work was divided into several parts. In the first stage, requirements were assumed for the design of the device, electrical elements chosen, and a diagram of their electrical connections is presented. In the second part, the created CAD model of the structure is presented and some of mechanical elements described. In order to check the strength of the structure, the FEM analysis of the device body was carried out. The penultimate part was to analyze the problem of the inverted pendulum, which allowed to separate the state space model into a base subsystem and a control stick subsystem necessary to develop the control for the platform. In the last part, a stabilizing algorithm based on the LQR regulator was prepared and the use of sensory fusion in the form of a Kalman filter was focused on in order to increase the accuracy of determining the angle of deflection of the structure. Finally, simulations were prepared in the Simulink environment in order to check the correctness of the prepared algorithm. The whole was crowned with a summary of the work and setting directions for further research.

PL

W artykule przedstawiono wyniki prac nad projektem dwukołowej samobalansującej platformy mobilnej przygotowanym w ramach pracy inżynierskiej. Celem stworzenia konstrukcji było umożliwienie zwiększania mobilności osoby dorosłej na niewielkich odległościach w zurbanizowanym środowisku. Całość prac projektowych podzielono na kilka części. W pierwszym etapie przedstawiono wymagania założone dla projektu urządzenia, dobrano elementy elektryczne oraz schemat ich połączeń elektrycznych. W drugiej części omówiono stworzony model CAD konstrukcji oraz jego elementy mechaniczne. W celu sprawdzenia wytrzymałości konstrukcji dokonano analizy MES korpusu urządzenia. Przedostatnią częścią było przeanalizowanie zagadnienia odwróconego wahadła, które pozwoliło na wyprowadzenie modelu przestrzeni stanu z rozdzieleniem na podsystemy bazy i drążka sterowniczego niezbędnego do opracowania sterowania dla platformy. W ostatniej części przygotowano algorytm stabilizujący na podstawie regulatora LQR oraz rozważano zastosowanie fuzji sensorycznej w postaci filtru Kalmana w celu zwiększenia dokładności określania kąta odchylenia konstrukcji. Na koniec przygotowano symulacje w środowisku Simulink w celu sprawdzenia poprawności przygotowanego algorytmu. Całość została zwieńczona podsumowaniem prac oraz wytyczeniem kierunków dalszych badań.

13

Promising wing vibration measurement system using MEMS IMUS and Kalman filter correction

Maamo M. S., Afonin A. A., Sulakov A. S.

International Journal of Applied Mechanics and Engineering

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2022

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Vol. 27, no. 2

143--157

EN

Nowadays, there is still a need for the development of a high-precision vibration measurement system for aircraft wings. By analyzing the wing vibration characteristics a lot of aviation studies could be conducted, including the wing health monitoring, the fluttering phenomenon and so on. This paper presents preliminary results of the research carried out toward building a promising system designed to measure vibration parameters of aircraft wing. Comparing it with the existing analogue systems, the proposed system features the use of approaches that are traditional for solving orientation and navigation problems for vibration measurements. The paper presents the basic structure of the system, the fundamentals of its operation, the mathematical errors models of its main components, the correction algorithms using optimal Kalman filter. Finally, the initial simulation results of system operation are shown, demonstrating the expected accuracy characteristics of the system, which confirms its effectiveness and the prospects of the chosen direction of research.

14

A Kalman filter with intermittent observations and reconstruction of data losses

Rhouma Taouba, Keller Jean-Yves, Abdelkrim Mohamed Naceur

International Journal of Applied Mathematics and Computer Science

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2022

|

Vol. 32, no. 2

241--253

EN

This paper deals with the problem of joint state and unknown input estimation for stochastic discrete-time linear systems subject to intermittent unknown inputs on measurements. A Kalman filter approach is proposed for state prediction and intermittent unknown input reconstruction. The filter design is based on the minimization of the trace of the state estimation error covariance matrix under the constraint that the state prediction error is decoupled from active unknown inputs corrupting measurements at the current time. When the system is not strongly detectable, a sufficient stochastic stability condition on the mathematical expectation of the random state prediction errors covariance matrix is established in the case where the arrival binary sequences of unknown inputs follow independent random Bernoulli processes. When the intermittent unknown inputs on measurements represent intermittent observations, an illustrative example shows that the proposed filter corresponds to a Kalman filter with intermittent observations having the ability to generate a minimum variance unbiased prediction of measurement losses.

15

Cascade tanks system identification for robust predictive control

Jakowluk Wiktor, Jaszczak Sławomir

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

|

Vol. 70, nr 6

art. no. e143646

EN

The main goal of estimating models for industrial applications is to guarantee the cheapest system identification. The requirements for the identification experiment should not be allowed to affect product quality under normal operating conditions. This paper deals with ensuring the required liquid levels of the cascade system tanks using the model predictive control (MPC) method. The MPC strategy was extended with the Kalman filter (KF) to predict the system’s succeeding states subject to a reference trajectory in the presence of both process and measurement noise covariances. The main contribution is to use the application-oriented input design to update the parameters of the model during system degradation. This framework delivers the least-costly identification experiment and guarantees high performance of the system with the updated model. The methods presented are evaluated both in the experiments on a real process and in the computer simulations. The results of the robust MPC application for cascade system water levels control are discussed.

16

Land vehicle navigation using low-cost integrated smartphone gnss mems and map matching technique

Mahmoud Mostafa, Abd Rabbou Mahmoud, El Shazly Adel

Artificial Satellites : Journal of Planetary Geodesy

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2022

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Vol. 57, No. 3

138--157

EN

The demand for smartphone positioning has grown rapidly due to increased positioning accuracy applications, such as land vehicle navigation systems used for vehicle tracking, emergency assistance, and intelligent transportation systems. The integration between navigation systems is necessary to maintain a reliable solution. High-end inertial sensors are not preferred due to their high cost. Smartphone microelectromechanical systems (MEMS) are attractive due to their small size and low cost; however, they suffer from long-term drift, which highlights the need for additional aiding solutions using road network that can perform efficiently for longer periods. In this research, the performance of the Xiaomi MI 8 smartphone's single-frequency precise point positioning was tested in kinematic mode using the between-satellite single-difference (BSSD) technique. A Kalman filter algorithm was used to integrate BSSD and inertial navigation system (INS)-based smartphone MEMS. Map matching technique was proposed to assist navigation systems in global navigation satellite system (GNSS)-denied environments, based on the integration of BSSD-INS and road network models applying hidden Marcov model and Viterbi algorithm. The results showed that BSSD-INS- map performed consistently better than BSSD solution and BSSD–INS integration, irrespective of whether simulated outages were added or not. The root mean square error (RMSE) values for 2D horizontal position accuracy when applying BSSD-INS-map integration improved by 29% and 22%, compared to BSSD and BSSD-INS navigation solutions, respectively, with no simulated outages added. The overall average improvement of proposed BSSD-INS-map integration was 91%, 96%, and 98% in 2D horizontal positioning accuracy, compared to BSSD-INS algorithm for six GNSS simulated signal outages with duration of 10, 20, and 30 s, respectively.

17

Disturbance-Kalman state for linear offset free MPC

Tuan Truong Thanh, Zabiri Haslinda, Mutalib Mohammad Ibrahim Abdul, Vo Dai-Viet N.

Archives of Control Sciences

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2022

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Vol. 32, No. 1

153--173

EN

In model predictive control (MPC), methods of linear offset free MPC are well established such as the disturbance model, the observer method and the state disturbance observer method. However, the observer gain in those methods is difficult to define. Based on the drawbacks observed in those methods, a novel algorithm is proposed to guarantee offset-free MPC under model-plant mismatches and disturbances by combining the two proposed methods which are the proposed Recursive Kalman estimated state method and the proposed Disturbance-Kalman state method. A comparison is made from existing methods to assess the ability of providing offset-free MPC on Wood-Berry distillation column. Results shows that the proposed offset free MPC algorithm has better disturbance rejection performance than the existing algorithms.

18

Assessing the multi-decadal shoreline dynamics along the Purba Medinipur Balasore coastal stretch, India by integrating remote sensing and statistical methods SK

Hossain Ariful, Mondal Ismail, Thakur Sandeep, Linh Nguyen Thi Thuy, Anh Duong Tran

Acta Geophysica

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2022

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Vol. 70, no 4

1701--1715

EN

Monitoring decadal shoreline change is essential to understand the influence of coastal processes on the coastline. The shoreline is constantly shaped by natural and anthropogenic factors, and so, it is critical to understand decadal trends. The prediction of future shoreline positions is a must for effective long-term coastal zone management. This study was conducted along a 90-km-stretch of the coastline from the mouth of the Haldi River (Purba Medinipur) in the Northeast to the Subarnarekha estuary (Balasore) in the Southwest. The primary objectives of the study were to analyze the decadal shoreline migration using the End Point Rate (EPR) method and then predict future shoreline change prediction using the Kalman Filter method. Shoreline positions were digitized after extracting the shorelines using Principal Component Analysis (PCA) from Multi-temporal (1990, 2000, 2010, and 2020) and Multisensor (Landsat TM, ETM+, and OLI) satellite data. A total of 887 transects were cast to compute change statistics of the time series shoreline. It was observed that the average shoreline change rate was −8.41 m/year in the periods of 1990–2000 and 2000–2010, and −8.80 m/year from 2010 to 2020. Accretion along this coastal stretch is caused by the growth of morphological features such as sand bars, beaches, and dunes. We also found that erosion occurred from 1990 to 2000 along the coastline of Bhograi, Ramnagar-I, Ramnagar-II, a few parts of Contai-I, Khejuri-I, and the Nandigram-I coastal block. Accretion mostly occurred due to Land reclamation in the Northern portion of Bhograi, Contai-1 blocks and Nandigram- I block from 2000 to 2010 and 2010 to2020. Root mean square error (RMSE) and Regression Coefficient values were computed for the future shoreline prediction of 2031 and 2041. The calculated RMSE value of±4.7 m and value of 0.97 shows a good relationship between the actual and predicted coastline of 2020. This study concludes that the coastline of Purba Medinipur-Balasore experienced severe erosion and needs management action and also proves the efficiency of the Digital Shoreline Analysis System (DSAS) tool for decadal analysis and prediction of shoreline change. The findings of this study may help the coastal planners, environmentalists, and coastal managers in preparing both short-term and long-term coastal zone management plans.

19

Mathematical modelling of construction of ship turning trajectory using autonomous bow thruster work and research of bow thruster control specifics

Kupraty Oleksandr

Scientific Journal of Gdynia Maritime University

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2021

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nr 118

7--23

EN

The article proposes a method of constructing the trajectory of a ship’s turn using a control device. Mathematical modelling of the turn trajectory is performed using MS Excel in conjunction with the MATLAB environment. To construct a trajectory, a conditional centre of turn will be used, it will be guided by a control device, such as a radio buoy, or a lighthouse with pre-known coordinates. The construction of this trajectory has two features: a step course change when rotated equal to a sector step, and the accuracy of the trajectory is achieved by using the Kalman filter, simplified to the amplification factor. The bow thruster moment is calculating using the bow thruster shoulder. The angular velocity of turning depends on the linear speed, therefore, the angular velocity can be adjusted not only by changing the bow thruster mode of operation, but also by changing the linear speed of the vessel. The article provides the program code for constructing a trajectory in the MATLAB environment, which takes its initial data from MS Excel. Therefore, the work forms the basic view of autonomous bow thruster control.

20

LQGi/LTR controller with integrators and feedforward controller applied to a Twin Rotor MIMO System

Senoussaoui Abderrahmane, Chenafa Mohammed, Sahraoui Mustapha, Kacimi Abderrahmene, Houcine Rachida

Przegląd Elektrotechniczny

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2021

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R. 97, nr 4

48--53

EN

This paper presents a comparison between LQGi and LQGi/LTR control of a Twin Rotor MIMO System (TRMS)(made by feedback instrument company). The Linear Quadratic Gaussian (LQG) means a linear quadratic regulator with KALMAN filter. LQG/LTR is an LQG controller with Loop Transfer Recovery. For both we introduced an integrator to deal with steady state errors and disturbances. A feed forward controller has been added to improve the tracking performances of the system. The results are in simulation and in real time.

PL

Przedstawiono porównanie sterowania LQG I LQG/LYR systemu MIMO z dwoama wirnikami TRMS. W sterowaniu LQG wykorzystano filtr Kalmana. Dodatkowo wprowadzono układ całkujący oraz sterownik typu feed forward. Sterowanie analizowano przez symulacje oraz eksperymentalnie.