Synthesis of LQR Controller Based on BAT Algorithm for Furuta Pendulum Stabilization

In this study, a controller design method based on the LQR method and BAT algorithm is presented for the Furuta pendulum stabilization system. Determine the LQR controller, it is often based on the designer's experience or using trial and error to find the Q, R matrices. The BAT search algorithm is based on the characteristics of the bat population in the wild. However, there are advantages to finding multivariate objective functions. The BAT algorithm has an improvement for the LQR controller to optimize the linear square function with fast response time, low energy consumption, overshoot, and a small number of oscillations. Swarm optimization algorithms have advantages in finding global extrema of multivariate functions. Therefore, with a large number of elements of the Q and R matrices, they can also be quickly found and these matrices still satisfy the Riccati equation. The controller with optimal parameters is verified through simulation results with different scenarios. The performance of the proposed controller is compared with a conventional LQR controller and implemented on a real system

On the Comparative Study of Some Mathematical Tools for Specific Sequences Design

In modern communication system, cryptography and automatic test patterns, some specific sequences with strictly defined properties are required to meet the application demands. [1,2,3,4…] These requirements are: Good pseudorandom (PN) properties (large period length, uniform distrbution…). Low periodic correlation property. Low aperiodic correlation property. Large linear complexity. Large cardinality (number of sequences in the set). Unfortunately, there is not any set of sequence satisfying all these requirements, despite the fact that a lot of efforts have been given for design such sequences. For this purpose, different mathematical tools have been widely used such as: matrix, d-transform and trace function representations. However, to the best of our knowledge, there has been no any comparative study on these mathematicals tools carried out so far! In this contribution, we try to fill some parts of this gap by considering some typical applications of these tools. The paper is constructed as below: In the introduction, the basic concepts and definitions of matrix, d-transform and trace are given (briefly). In section II, some typical applications (for demonstration) will be shown. In this regard, we will give some discussions and suggestions for choosing the appropriate mathematical tools for each application. Especially, in section III, we will show the relationship (interchanging or equivalencies) between them. Keywords: specific sequences, mathematical tool, matrix, d-transform and trace

Comparing Labor Productivity of Vietnam to Some Asian Countries

In Vietnam, social labor productivity is an indicator of the National Statistical Indicator System (specified in the Law on Statistics), which is calculated by the average GDP per employed worker per year. Research results show that in the 2016-2020 period, labor productivity of the whole economy has improved markedly, with an average increase of 5.78%/year in the 2016-2020 period. However, Vietnam’s labor productivity still has internal limitations that have not been overcome. In comparison with selected Asian countries, Vietnam’s labor productivity has a low absolute value despite its relatively high growth since 1991. In most of the sectors compared, it is basically at the lowest level. As a result, proposing solutions to improve and enhance labor productivity aimed at promoting sustainable economic growth in Vietnam in the coming time is an urgent issue for the development of the country

A Hardware Oriented Method to Generate and Evaluate Nonlinear Interleaved Sequences with Desired properties

It is well known that the combinatorial structure, algebraic structure and D-transform based method render the nonlinear sequences with good autocorrelation function (ACF) and great linear complexity (LC). However, “all sequences” are not equal even if they are “born” by the same method! In this paper the big inequalities regarding LC of these sequences are shown based on a hardware oriented method (D-transform). In order to get the right sequences some more extensive simulations and trade off are needed. That is why this paper is represented here with above Title. Keywords: cryptography, mobile communications, security, watermarking, D-transfor

Formation and functional properties of protein–polysaccharide electrostatic hydrogels in comparison to protein or polysaccharide hydrogels

Protein and polysaccharide mixed systems have been actively studied for at least 50 years as they can be assembled into functional particles or gels. This article reviews the properties of electrostatic gels, a recently discovered particular case of associative protein–polysaccharide mixtures formed through associative electrostatic interaction under appropriate solution conditions (coupled gel). This review highlights the factors influencing gel formation such as protein–polysaccharide ratio, biopolymer structural characteristics, final pH, ionic strength and total solid concentration. For the first time, the functional properties of protein–polysaccharide coupled gels are presented and discussed in relationship to individual protein and polysaccharide hydrogels. One of their outstanding characteristics is their gel water retention. Up to 600 g of water per g of biopolymer may be retained in the electrostatic gel network compared to a protein gel (3–9 g of water per g of protein). Potential applications of the gels are proposed to enable the food and non-food industries to develop new functional products with desirable attributes or new interesting materials to incorporate bioactive molecules

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

Model Updating for Large-Scale Railway Bridge Using Grey Wolf Algorithm and Genetic Alghorithms

This paper proposes a novel hybrid algorithm to deal with an inverse problem of a large-scale truss bridge. Grey Wolf Optimization (GWO) Algorithm is a well-known and widely applied metaheuristic algorithm. Nevertheless, GWO has two major drawbacks. First, this algorithm depends crucially on the positions of the leading Wolf. If the position of the leaderis far from the best solution, the obtained results are poor. On the other hand, GWO does not own capacities to improve the quality of new generations if elements are trapped into local minima. To remedy the shortcomings of GWO, we propose a hybrid algorithm combining GWO with Genetic Algorithm (GA), termed HGWO-GA. This proposed method contains two key features (1) based on crossover and mutation capacities, GA is first utilized to generate the high-quality elements (2) after that, the optimization capacity of GWO is employed to seek the optimal solutions. To assess the effectiveness of the proposed approach, a large-scale truss bridge is employed for model updating. The obtained results show that HGWO-GA not only provides a good agreement between numerical and experimental results but also outperforms traditional GWO in terms of accuracy

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method