Improved Polynomial Fuzzy Modeling and Controller with Stability Analysis for Nonlinear Dynamical Systems

This study presents an improved model and controller for nonlinear plants using polynomial fuzzy model-based (FMB) systems. To minimize mismatch between the polynomial fuzzy model and nonlinear plant, the suitable parameters of membership functions are determined in a systematic way. Defining an appropriate fitness function and utilizing Taylor series expansion, a genetic algorithm (GA) is used to form the shape of membership functions in polynomial forms, which are afterwards used in fuzzy modeling. To validate the model, a controller based on proposed polynomial fuzzy systems is designed and then applied to both original nonlinear plant and fuzzy model for comparison. Additionally, stability analysis for the proposed polynomial FMB control system is investigated employing Lyapunov theory and a sum of squares (SOS) approach. Moreover, the form of the membership functions is considered in stability analysis. The SOS-based stability conditions are attained using SOSTOOLS. Simulation results are also given to demonstrate the effectiveness of the proposed method

SNPs genotyping technologies and their applications in farm animals breeding programs: review

Single nucleotide polymorphisms (SNPs) are DNA sequence variations that occur when a single nucleotide: adenine (A), thymine (T), cytosine (C) or guanine (G) in the genome sequence is altered. Traditional and high throughput methods are two main strategies for SNPs genotyping. The SNPs genotyping technologies provide powerful resources for animal breeding programs.Genomic selection using SNPs is a new tool for choosing the best breeding animals. In addition, the high density maps using SNPs can provide useful genetic tools to study quantitative traits genetic variations. There are many sources of SNPs and exhaustive numbers of methods of SNP detection to be considered. For many traits in farm animals, the rate of genetic improvement can be nearly doubled when SNPs information is used compared to the current methods of genetic evaluation. The goal of this review is to characterize the SNPs genotyping methods and their applications in farm animals breeding

Offline neural network based fault tolerant control for vertical tail damaged aircraft

This paper investigates the offline neural network based-fault tolerant control for an aircraft that suffers vertical-tail damage. First, the damaged model of the aircraft is obtained, and the external disturbance is estimated by a disturbance observer then, an optimal control scheme is proposed to control the aircraft in nominal condition. This optimal control scheme is developed into faulty condition by the offline neural networks. The simulation results show the effectiveness of the proposed method in comparison to the existing methods in the literature. Key Words—fault tolerant control, vertical tail damage, neural networks, linear quadratic regulator, offline learning

Novel genetic variants data for adaptation to hypoxia in native chickens

Abstract Objective The genomic response and the role of genetic variants in hypoxia condition are always interesting issues about adaption pathways at genomic level. Herein, we carried out a comparative genomic study between highland and lowland native chickens, in order to identify the adaptive variants in hypoxia condition. We generated more than 20 million genetic variants in highland and lowland chickens. Finally, 3877 SNVs including the mtDNA ones, were discovered as novel adaptive genetic variants. The generated data set can provide new insight about mechanism of adaptation to hypoxia at genomic level. Data description To investigate the role of genetic variants in adaptation to hypoxia, 10 whole-genome sequencing data sets associated to highland and lowland native chickens were provided. DNA was extracted by salting-out protocol. Paired-end 125 bp short reads were sequenced by Illumina Hiseq 2000. Variants calling of highland and lowland native chickens were performed by fix ploidy algorithm in CLC Genomic Workbench. Total genetic variants of highland chickens were compared to lowland chickens in order to identify the differential genetic variants (DGVs) between highland and lowland chickens. In this way, 3877 novel SNVs (VCF format) including the mtDNA ones, were deposited at EBI database ( https://identifiers.org/ena.embl:ERZ491574 ) for the first time

A modified fruit fly optimization algorithm and its application to control of robot manipulators

This paper presents a new Modified Fruit Fly Optimization Algorithm (MFOA) which is used to find the optimal PID controllers parameters applied to control a two-link robotic manipulator. The proposed new distribution law in MFOA for some of the fruit flies improves searching diversity in earlier iterations and increases solution precession in last iterations. In order to apply the PID controllers to the robot manipulator, a nonlinear feedback linearization control technique is employed which can fully linearize and decouple nonlinear robot's dynamics. Simulation results confirm that the MFOA-PID controller can achieve better closed-loop system responses with respect to the original FOA-PID controller