Hybrid Genetic Algorithm and Kalman Filter Approach to Estimate the Clamping Force of Electro-Mechanical Brake

In thispaper, a hybrid genetic algorithm (GA) and Kalman filter approach to combining motor encoder and current sensor models is presented to accurate estimate the clamping force of an electro-mechanical brake (EMB). Elimination of the clamping force sensor and measurement cables results in lower cost and increased reliability of an EMB system, including its electric motor.A Kalman filter is a special kind of observer that provides optimal filtering of the measurement noise and inside the system if the covariances of these noises are known. The proposed combined estimator is based on Kalman filter optimized by GA in which the motor encoder is used in a dynamic stiffness model and the motor current sensor is used to give measurement updates in a torque balance model. A real-coded GA is used to optimize the noise matrices and improve the performance of the Kalman filter. Experimental results show that, by using the proposed estimator, the virtual clamping force sensor can handle highly dynamic situations, making it suitable for possible use in sensorless fault-tolerant control. It is shown that the proposed combined estimator improves the root mean square error (RMSE) performance. The developed estimator can be used in real vehicle environments because it can adapt to parameter variations

Reversibly controlled ternary polar states and ferroelectric bias promoted by boosting square???tensile???strain

Interaction between dipoles often emerges intriguing physical phenomena, such as exchange bias in the magnetic heterostructures and magnetoelectric effect in multiferroics, which lead to advances in multifunctional heterostructures. However, the defect-dipole tends to be considered the undesired to deteriorate the electronic functionality. Here, we report deterministic switching between the ferroelectric and the pinched states by exploiting a new substrate of cubic perovskite, BaZrO3, which boosts square-tensile-strain to BaTiO3 and promotes four-variants in-plane spontaneous polarization with oxygen vacancy creation. First-principles calculations propose a complex of an oxygen vacancy and two Ti3+ ions coins a charge-neutral defect-dipole. Cooperative control of the defect-dipole and the spontaneous polarization reveals ternary in-plane polar states characterized by biased/pinched hysteresis loops. Furthermore, we experimentally demonstrate that three electrically controlled polar-ordering states lead to switchable and non-volatile dielectric states for application of non-destructive electro-dielectric memory. This discovery opens a new route to develop functional materials via manipulating defect-dipoles and offers a novel platform to advance heteroepitaxy beyond the prevalent perovskite substrates

Structural and mutational analyses of psychrophilic and mesophilic adenylate kinases highlight the role of hydrophobic interactions in protein thermal stability

Protein thermal stability is an important field since thermally stable proteins are desirable in many academic and industrial settings. Information on protein thermal stabilization can be obtained by comparing homologous proteins from organisms living at distinct temperatures. Here, we report structural and mutational analyses of adenylate kinases (AKs) from psychrophilic Bacillus globisporus (AKp) and mesophilic Bacillus subtilis (AKm). Sequence and structural comparison showed suboptimal hydrophobic packing around Thr26 in the CORE domain of AKp, which was replaced with an Ile residue in AKm. Mutations that improved hydrophobicity of the Thr residue increased the thermal stability of the psychrophilic AKp, and the largest stabilization was observed for a Thr-to-Ile substitution. Furthermore, a reverse Ile-to-Thr mutation in the mesophilic AKm significantly decreased thermal stability. We determined the crystal structures of mutant AKs to confirm the impact of the residue substitutions on the overall stability. Taken together, our results provide a structural basis for the stability difference between psychrophilic and mesophilic AK homologues and highlight the role of hydrophobic interactions in protein thermal stability

Protection Strategies Against False Data Injection Attacks with Uncertain Information on Electric Power Grids

False data injection attacks have recently been introduced as one of important issues related to cyber-attacks on electric power grids. These attacks aim to compromise the readings of multiple power meters in order to mislead the operation and control centers. Recent studies have shown that if a malicious attacker has complete knowledge of the power grid topology and branch admittances, s/he can adjust the false data injection attack such that the attack remains undetected and successfully passes the bad data detection tests that are used in power system state estimation. In this paper, we investigate that a practical false data injection attack is essentially a cyber-attack with uncertain information due to the attackers lack of knowledge with respect to the power grid parameters because the attacker has limited physical access to electric facilities and limited resources to compromise meters. We mathematically formulated a method of identifying the most vulnerable locations to false data injection attack. Furthermore, we suggest minimum topology changes or phasor measurement units (PMUs) installation in the given power grids for mitigating such attacks and indicate a new security metrics that can compare different power grid topologies. The proposed metrics for performance is verified in standard IEEE 30-bus system. We show that the robustness of grids can be improved dramatically with minimum topology changes and low cost. © The Korean Institute of Electrical Engineers.1

Structural analysis for a lightweight model of large sheet material transfer robot

Currently most of the products being produced have been developed in such a way as to develop an initial model for product stabilization and to improve various components of the product. Among the various components that make up the product, the main improvement method for the mechanical element is made by lightweight the product. Lightweight has become a major concern for the industry as a whole because of it is possible to obtain not only the cost required for the production of the product but also the energy saving effect necessary for the use of the product. As a general method of lightweight of the product, there are a method of reducing the volume by removing unnecessary parts of the existing product through a design change and a method of reflecting a material having a density lower than that of the material constituting the existing product. The above-mentioned methods for lightweight are factors affecting the structural stability of the product, and excessive lightweight affects the breakage and life of the product. Therefore, it is necessary to consider the utilization purpose and the use environment of the product when approaching to reduce the weight of the product, and verification of the lightweight model is required before the production. In this paper, we perform static analysis for structural stability of lightweight transfer robot that using in the tandem press line which produces the product through by multiple pressing process

Slc6a20a Heterozygous and Homozygous Mutant Mice Display Differential Behavioral and Transcriptomic Changes

Copyright © 2022 Kim, Roh, Kim, Kang, Bae and Kim.SLC6A20A is a proline and glycine transporter known to regulate glycine homeostasis and NMDA receptor (NMDAR) function in the brain. A previous study found increases in ambient glycine levels and NMDA receptor-mediated synaptic transmission in the brains of Slc6a20a-haploinsufficient mice, but it remained unknown whether Slc6a20a deficiency leads to disease-related behavioral deficits in mice. Here, we report that Slc6a20a heterozygous and homozygous mutant mice display differential behavioral phenotypes in locomotor, repetitive behavioral, and spatial and fear memory domains. In addition, these mice show differential transcriptomic changes in synapse, ribosome, mitochondria, autism, epilepsy, and neuron-related genes. These results suggest that heterozygous and homozygous Slc6a20a deletions in mice lead to differential changes in behaviors and transcriptomes.11Nsciescopu

Nonlinear Identification of Electronic Brake Pedal Behavior Using Hybrid GMDH and Genetic Algorithm in Brake-By-Wire System

In this paper, we represent a nonlinear identification of electronic brake pedal behavior in the brake-by-wire (BBW) system based on hybrid group method of data handling (GMDH) and genetic algorithm (GA). A GMDH is a kind of multi-layer network with a structure that is determined through training and which can express nonlinear dynamics as a mathematical model. The GA is used in the GMDH, enabling each neuron to search for its optimal set of connections with the preceding layer. The results obtained with this hybrid approach were compared with different nonlinear system identification methods. The experimental results showed that the hybrid approach performs better than the other methods in terms of root mean square error (RMSE) and correlation coefficients. The hybrid GMDH/GA approach was effective for modeling and predicting the brake pedal system under random braking conditions. © The Korean Institute of Electrical Engineers.1

Conformational dynamics of adenylate kinase in crystals

Adenylate kinase is a ubiquitous enzyme in living systems and undergoes dramatic conformational changes during its catalytic cycle. For these reasons, it is widely studied by genetic, biochemical, and biophysical methods, both experimental and theoretical. We have determined the basic crystal structures of three differently liganded states of adenylate kinase from Methanotorrus igneus, a hyperthermophilic organism whose adenylate kinase is a homotrimeric oligomer. The multiple copies of each protomer in the asymmetric unit of the crystal provide a unique opportunity to study the variation in the structure and were further analyzed using advanced crystallographic refinement methods and analysis tools to reveal conformational heterogeneity and, thus, implied dynamic behaviors in the catalytic cycle

A Soft Computing Approach for Brake Pedal Behavior Identification in Brake-By-Wire System

This paper represents a nonlinear identification of the electronic brake pedal behavior in brake-by-wire (BBW) system. The electro-mechanical brake (EMB) in BBW system has become an advanced automotive braking system that enhanced performances without a mechanical or hydraulic backup. We developed the BBW system and the Group Method of Data Handling (GMDH) algorithm is also applied because of the brake pedal sensor output depends on many nonlinear interactions. After analyzing the experiment results, we found that GMDH algorithm can effectively identify the electronic brake pedal system