scholarly journals Investigation of electric generator robust algorithm under measurement noises

2018 ◽  
pp. 204-209
Author(s):  
Igor B. Furtat ◽  
Artem N. Nekhoroshikh
Keyword(s):  
Control Algorithm ◽  
Nonlinear Differential Equations ◽  
Frequency Measurement ◽  
Unknown Parameters ◽  
Third Order ◽  
Electric Generator ◽  
Bounded Disturbances ◽  
Measurement Noises ◽  
Load Angle

The paper considers the investigation of a novel robust control algorithm of an electric generator with unknown parameters under bounded disturbances and high-frequency measurement noises. It is assumed that only the load angle is available for measurement, but not the rotor speed. The electric generator model is described by a system of third-order nonlinear differential equations with algebraic coupling ones. The proposed algorithm consisting of static and dynamical terms is based on the separation of the filtering and estimating properties. Differently from existing results the proposed scheme provides the opportunity to control independently the quality of filtering and stabilization. Investigations show that the proposed algorithm attenuates parametric uncertainties and disturbances with accuracy that can be reduced by tuning algorithm parameters.

Synchronization of the Electric Power Network in the Conditions of High-Frequency Measurement Noises

2020 ◽  
Vol 21 (10) ◽  
pp. 584-594
Author(s):  
I. B. Furtat ◽  
V. N. Nekhoroshikh ◽  
P. A. Gushchin ◽  
Y. V. Chugina
Keyword(s):  
High Frequency ◽  
Electrical Power ◽  
Sudden Change ◽  
Frequency Measurement ◽  
Power Network ◽  
Unknown Parameters ◽  
Measurement Noises ◽  
Simulation Results ◽  
The Stability

The problem of robust synchronization of the electrical power network with unknown parameters is considered in the present paper. The load angles of each generator with superimposed additive high frequency noises are available for measurement. An algorithm has been synthesized to reduce the influence of noises on measurement signals and to ensure synchronization of the network in normal mode and in emergency situations associated with a sudden change in the conuctivity of power lines. To synthesize the control algorithm, the new approach is used which makes it possible to independently control the quality of noise filtering and the quality of the stabilization error of the output variable. The conditions guaranteeing the stability of the system are obtained. The simulation results have shown that the designed control system of a network of electric generators, when only noisy indications of load angles are available for measurement, provides better transient quality indicators compared to schemes of R. Ortega (France) and D. Hill (Australia), where the entire state vector is available to measurements and the parameters of the generator model are partially known. Modeling also showed that the proposed algorithm ensures the stability of a closed-loop system if there are unmodeled dynamics in network model. We also note that under conditions of random measurement noises, the control goal cannot be guaranteed due to the unlimited nature of the noises, however, the simulation results illustrate the satisfactory quality of transients with nonzero random signals in noises.

Asymptotics for third-order nonlinear differential equations: Non-oscillatory and oscillatory cases

2021 ◽  
pp. 1-19
Author(s):  
Calogero Vetro ◽  
Dariusz Wardowski
Keyword(s):  
Differential Equation ◽  
Differential Equations ◽  
Order Differential Equation ◽  
Nonlinear Differential Equations ◽  
Oscillatory Behavior ◽  
Third Order ◽  
First Order ◽  
Third Order Differential Equation ◽  
Comparison Technique ◽  
First Order Differential Equations

We discuss a third-order differential equation, involving a general form of nonlinearity. We obtain results describing how suitable coefficient functions determine the asymptotic and (non-)oscillatory behavior of solutions. We use comparison technique with first-order differential equations together with the Kusano–Naito’s and Philos’ approaches.

Research of H∞ Robust Control for the Giant Die Forging Hydraulic Press’s Synchronous Control System under the Uncertainty Coefficient

2012 ◽  
Vol 190-191 ◽  
pp. 819-824 ◽  
Author(s):  
Ying Jian Deng ◽  
Zhong Wei Liu
Keyword(s):  
Control System ◽  
Robust Control ◽  
Control Algorithm ◽  
Hydraulic Press ◽  
National Defense ◽  
Synchronous Control ◽  
Performance Quality ◽  
System Synchronization ◽  
Uncertainty Coefficient

The giant hydraulic die press is our country national defense and the infrastructure essential equipment, the synchronous control system is the essential device to the giant forging hydraulic press, its synchronization control performance quality is good or bad will directly determine the quality of the product. This article through the proof of the theorem, gives the specific steps to achieve H∞ robust control algorithm. The simulation results show that: this control strategy has good inhibition to the change of system parameters, robustness is very strong, can well eliminate the system synchronization error.

scholarly journals Asymptotic Dichotomy in a Class of Third-Order Nonlinear Differential Equations with Impulses

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Kun-Wen Wen ◽  
Gen-Qiang Wang ◽  
Sui Sun Cheng
Keyword(s):  
Differential Equation ◽  
Differential Equations ◽  
Nonlinear Differential Equation ◽  
Nonlinear Differential Equations ◽  
Functional Differential Equations ◽  
Higher Order ◽  
Third Order ◽  
Order Nonlinear Differential Equation ◽  
Functional Differential

Solutions of quite a few higher-order delay functional differential equations oscillate or converge to zero. In this paper, we obtain several such dichotomous criteria for a class of third-order nonlinear differential equation with impulses.

scholarly journals Intelligent Routing Control for MANET Based on Reinforcement Learning

2018 ◽  
Vol 232 ◽  
pp. 04002
Author(s):  
Fang Dong ◽  
Ou Li ◽  
Min Tong
Keyword(s):  
Reinforcement Learning ◽  
Control Algorithm ◽  
Rapid Development ◽  
Selection Strategy ◽  
Performance Simulation ◽  
Multiple Parameters ◽  
Intelligent Routing ◽  
Routing Control ◽  
The Cost

With the rapid development and wide use of MANET, the quality of service for various businesses is much higher than before. Aiming at the adaptive routing control with multiple parameters for universal scenes, we propose an intelligent routing control algorithm for MANET based on reinforcement learning, which can constantly optimize the node selection strategy through the interaction with the environment and converge to the optimal transmission paths gradually. There is no need to update the network state frequently, which can save the cost of routing maintenance while improving the transmission performance. Simulation results show that, compared with other algorithms, the proposed approach can choose appropriate paths under constraint conditions, and can obtain better optimization objective.

scholarly journals Efficient gradient-based parameter estimation for dynamic models using qualitative data

2021 ◽  
Author(s):  
Leonard Schmiester ◽  
Daniel Weindl ◽  
Jan Hasenauer
Keyword(s):  
Parameter Estimation ◽  
Qualitative Data ◽  
Dynamic Models ◽  
Unknown Parameters ◽  
Differential Equation Models ◽  
Gradient Calculation ◽  
Order Of Magnitude ◽  
Gradient Based ◽  
Objective Function Values

AbstractMotivationUnknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are rare and suffer from bad scaling and convergence.ResultsHere, we propose an efficient and reliable framework for estimating the parameters of ordinary differential equation models from qualitative data. In this framework, we derive a semi-analytical algorithm for gradient calculation of the optimal scaling method developed for qualitative data. This enables the use of efficient gradient-based optimization algorithms. We demonstrate that the use of gradient information improves performance of optimization and uncertainty quantification on several application examples. On average, we achieve a speedup of more than one order of magnitude compared to gradient-free optimization. Additionally, in some examples, the gradient-based approach yields substantially improved objective function values and quality of the fits. Accordingly, the proposed framework substantially improves the parameterization of models from qualitative data.AvailabilityThe proposed approach is implemented in the open-source Python Parameter EStimation TOolbox (pyPESTO). All application examples and code to reproduce this study are available at https://doi.org/10.5281/zenodo.4507613.

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