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- 저자 : Ankur Goel (검색결과 2 건)
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Ankur Goel,Akhilesh Swarup 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.1
Active disturbance rejection control (ADRC) is a unique control strategy that combines the effectiveness of error driven PID controller, usefulness of state observer and strength of nonlinear feedback. This control algorithm, not only actively (online) estimates but also compensates the effects of unknown internal and external disturbances, present inherently in the plant with the help of a well-tuned extended state observer (ESO). Although, the classical solution to the parameter tuning performed by using parameterization technique provides good solution, it is not optimal for having desired performance specifications. Consequently, it became imperative to have intelligent tuning technique to achieve optimized solution to parameter tuning problem. In this regards, the Evolutionary Algorithms (EA), inspired by natural system and based on swarm intelligence, are proven to be the best tool to find the optimized solution of multi-dimensional problems. This paper presents an application of an EA optimized ADRC controller on an uncertain 2-DoF revolute-prismatic (RP) robotic manipulator for efficient trajectory tracking and parametric robustness. Eventually, the conventional ADRC design problem is converted into a special optimization problem for finding the optimal controller tuning parameters. To accomplish this task, two well-known EA’s viz. Particle Swarm Optimization (PSO) and Bacteria Foraging Optimization (BFO) are implemented and performance of EA based controller-plant configuration is individually analyzed for each algorithm. The results of this note illustrate the benefits and weakness of the EA for implementing ADRC on MIMO systems. The performance of both the optimization techniques is compared in terms of computational time and convergence efficiency. Further, the optimized controllers are tested for the robustness in presence of disturbance and sensor noise to imitate real engineering. MATLAB based simulation results are presented and compared to demonstrate the effectiveness of both the EA's in designing an ADRC controller for improving manipulator tracking ability.
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Virmani, Richa,Sajid, Andaleeb,Singhal, Anshika,Gaur, Mohita,Joshi, Jayadev,Bothra, Ankur,Garg, Richa,Misra, Richa,Singh, Vijay Pal,Molle, Virginie,Goel, Ajay K.,Singh, Archana,Kalia, Vipin C.,Lee, Ju American Society for Biochemistry and Molecular Bi 2019 The Journal of biological chemistry Vol.294 No.22
<P><I>Bacillus anthracis</I> is the causative agent of anthrax in humans, bovine, and other animals. <I>B. anthracis</I> pathogenesis requires differentiation of dormant spores into vegetative cells. The spores inherit cellular components as phenotypic memory from the parent cell, and this memory plays a critical role in facilitating the spores' revival. Because metabolism initiates at the beginning of spore germination, here we metabolically reprogrammed <I>B. anthracis</I> cells to understand the role of glycolytic enzymes in this process. We show that increased expression of enolase (Eno) in the sporulating mother cell decreases germination efficiency. Eno is phosphorylated by the conserved Ser/Thr protein kinase PrkC which decreases the catalytic activity of Eno. We found that phosphorylation also regulates Eno expression and localization, thereby controlling the overall spore germination process. Using MS analysis, we identified the sites of phosphorylation in Eno, and substitution(s) of selected phosphorylation sites helped establish the functional correlation between phosphorylation and Eno activity. We propose that PrkC-mediated regulation of Eno may help sporulating <I>B. anthracis</I> cells in adapting to nutrient deprivation. In summary, to the best of our knowledge, our study provides the first evidence that in sporulating <I>B. anthracis</I>, PrkC imprints phenotypic memory that facilitates the germination process.</P>
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