Automated Compensation Scheme Design for Operational Amplifier via Bayesian Optimization

The 20S Proteasome is a macromolecule responsible for the chemical step in the ubiquitin-proteasome system of degrading unnecessary and unused proteins of the cell. It plays a central role both in the rapid growth of cancer cells as well as in viral infection cycles. Herein, we present a computational study of the acid-base equilibria in an active site of the human proteasome, an aspect which is often neglected despite the crucial role protons play in the catalysis. As example substrates, we take the inhibition by epoxy and boronic acid containing warheads. We have combined cluster quantum mechanical calculations, replica exchange molecular dynamics and Bayesian optimization of non-bonded potential terms in the inhibitors. In relation to the latter, we propose an easily scalable approach to the reevaluation of non-bonded potentials making use of QM/MM dynamics information. Our results show that coupled acid-base equilibria need to be considered when modeling the inhibition mechanism. The coupling between a neighboring lysine and the reacting threonine is not affected by the presence of the inhibitor.

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Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

Engineering and Technology Journal ◽

10.30684/etj.v38i9a.1339 ◽

2020 ◽

Vol 38 (9A) ◽

pp. 1342-1351

Author(s):

Musadaq A. Hadi ◽

Hazem I. Ali

Keyword(s):

Reference Model ◽

Feedback System ◽

Optimization Method ◽

Feedback Systems ◽

Model Reference ◽

Scheme Design ◽

Model Reference Control ◽

Control Scheme ◽

Lyapunov Stability Analysis ◽

Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

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Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

Automation. Modern Techologies ◽

10.36652/0869-4931-2020-74-3-129-134 ◽

2020 ◽

pp. 129-134

Keyword(s):

Predictive Model ◽

Unmanned Aerial Vehicle ◽

Predictive Models ◽

Navigation System ◽

Error Compensation ◽

Compensation Scheme ◽

Radar Images ◽

Aerial Vehicle ◽

System Errors ◽

Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

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