scholarly journals Control of oscillations in two-rotor cyberphysical vibration units with time-varying observer

2020 ◽  
pp. 206-213
Author(s):  
Olga P. Tomchina
Keyword(s):  
Control Algorithms ◽  
Time Varying ◽  
Rotor Vibration ◽  
Synchronous Rotation ◽  
Simulation Results ◽  
Control Of Oscillations ◽  
Special Control ◽  
Speed Gradient

In this paper the control of oscillations in the two-rotor vibration unit is studied. It is assumed that the velocity of the oscillation of the platform cannot be accurately measured. The time-varying observer is proposed to restore it. In order to guarantee stability of the frequency and amplitude of oscillations of the vibrating parts of a two-rotor vibration unit special control algorithms based on speed-gradient methodology. Simulation results confirm stability of the synchronous rotation modes of the unbalanced rotors of the vibration unit.

scholarly journals Control of vibrational field in a vibration unit: influence of drive dynamics

2019 ◽  
pp. 298-306
Author(s):  
Olga P. Tomchina
Keyword(s):  
Feedback Control ◽  
Closed Loop ◽  
Control Algorithms ◽  
Rotor Vibration ◽  
Mechatronic Systems ◽  
Simulation Results ◽  
Drive Dynamics

In the paper the problem of feedback control of vibrational fields in a vibration unit is analyzed taking into account the influence of the drive dynamics in the case when the control algorithms are designed when the drive dynamics are neglected. The performance of the closed loop mechatronic systems is examined by simulation for the model of the two-rotor vibration unit SV-2M. Comparison of simulation results for two cases (drive dynamics are neglected or taken into account) is performed.

Adaptive control of time-varying non-linear plants by speed-gradient algorithms

2019 ◽  
pp. 37-44 ◽  
Author(s):  
O. P. Tomchina ◽  
D. N. Polyakhov ◽  
O. I. Tokareva ◽  
A. L. Fradkov
Keyword(s):  
Adaptive Control ◽  
Adaptive Systems ◽  
Reference Model ◽  
Maximum Deviation ◽  
Model Parameters ◽  
Time Varying ◽  
System Solution ◽  
Non Linear ◽  
Initial Uncertainty ◽  
Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

scholarly journals Time-Varying Impedance Control of Port Hamiltonian System with a New Energy-Storing Tank

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Min Zheng ◽  
Tangqing Yuan ◽  
Tao Huang
Keyword(s):  
Control Method ◽  
Impedance Control ◽  
Conservative System ◽  
Time Varying ◽  
Control Performance ◽  
Singularity Problem ◽  
Numerical Examples ◽  
New Energy ◽  
Simulation Results ◽  
New Framework

In order to guarantee the passivity of a kind of conservative system, the port Hamiltonian framework combined with a new energy tank is proposed in this paper. A time-varying impedance controller is designed based on this new framework. The time-varying impedance control method is an extension of conventional impedance control and overcomes the singularity problem that existed in the traditional form of energy tank. The validity of the controller designed in this paper is shown by numerical examples. The simulation results show that the proposed controller can not only eliminate the singularity problem but can also improve the control performance.

Iterative learning algorithm with a quadratic criterion for linear time-varying systems

2002 ◽  
Vol 216 (3) ◽  
pp. 309-316 ◽  
Author(s):  
S N Huang ◽  
K K Tan ◽  
T H Lee
Keyword(s):  
Learning Algorithm ◽  
Linear Time ◽  
Tracking Error ◽  
Iterative Learning ◽  
Tracking Performance ◽  
Time Varying ◽  
Control Scheme ◽  
Time Varying Systems ◽  
Simulation Results ◽  
Learning Law

A novel iterative learning controller for linear time-varying systems is developed. The learning law is derived on the basis of a quadratic criterion. This control scheme does not include package information. The advantage of the proposed learning law is that the convergence is guaranteed without the need for empirical choice of parameters. Furthermore, the tracking error on the final iteration will be a class K function of the bounds on the uncertainties. Finally, simulation results reveal that the proposed control has a good setpoint tracking performance.

scholarly journals Mechatronic Device for Locomotor Training

2016 ◽  
Vol 10 (4) ◽  
pp. 310-315 ◽  
Author(s):  
Sławomir Duda ◽  
Damian Gąsiorek ◽  
Grzegorz Gembalczyk ◽  
Sławomir Kciuk ◽  
Arkadiusz Mężyk
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Measurement Data ◽  
Healthy Person ◽  
Control Algorithms ◽  
Design Team ◽  
Locomotor Training ◽  
Interdisciplinary Design ◽  
Machine Control ◽  
Simulation Results

Abstract This paper presents a novel mechatronic device to support a gait reeducation process. The conceptual works were done by the interdisciplinary design team. This collaboration allowed to perform a device that would connect the current findings in the fields of biomechanics and mechatronics. In the first part of the article shown a construction of the device which is based on the structure of an overhead travelling crane. The rest of the article contains the issues related to machine control system. In the prototype, the control of drive system is conducted by means of two RT-DAC4/PCI real time cards connected with a signal conditioning interface. Authors present the developed control algorithms and optimization process of the controller settings values. The summary contains a comparison of some numerical simulation results and experimental data from the sensors mounted on the device. The measurement data were obtained during the gait of a healthy person.

Traffic Fuzzy Controller's Improvement Based on Self-Adaptive Optimal Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1414-1417
Author(s):  
Zhi Yi Xu ◽  
Da Lu Guan ◽  
Ai Long Fan
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Fuzzy Controller ◽  
Optimal Algorithm ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Time Varying ◽  
Large Scale Systems ◽  
Simulation Results ◽  
Self Adaptive

The transport system is a nonlinear, time-varying, lagging large-scale systems. Fuzzy control does not need to build a precise mathematical model, can be easily integrated people's thinking and experience, and is suitable for applications in the traffic signal control system. Here,a self-adaptive optimal algorithm was used to improve the traditional fuzzy controller. Simulation results show that the improved system has higher availability.

Adaptive Synchronization in Unknown Stochastic Chaotic Neural Networks with Mixed Time-Varying Delays

2011 ◽  
pp. 289-313
Author(s):  
Jian-an Fang ◽  
Yang Tang
Keyword(s):  
Neural Networks ◽  
Sufficient Conditions ◽  
Stochastic Perturbation ◽  
Adaptive Synchronization ◽  
Output Coupling ◽  
Time Varying ◽  
Connection Weight ◽  
Chaotic Neural Networks ◽  
Simulation Results ◽  
Feedback Techniques

Neural networks (NNs) have been useful in many fields, such as pattern recognition, image processing etc. Recently, synchronization of chaotic neural networks (CNNs) has drawn increasing attention due to the high security of neural networks. In this chapter, the problem of synchronization and parameter identification for a class of chaotic neural networks with stochastic perturbation via state and output coupling, which involve both the discrete and distributed time-varying delays has been investigated. Using adaptive feedback techniques, several sufficient conditions have been derived to ensure the synchronization of stochastic chaotic neural networks. Moreover, all the connection weight matrices can be estimated while the lag synchronization and complete synchronization is achieved in mean square at the same time. The corresponding simulation results are given to show the effectiveness of the proposed method.

Comparison of Damped Velocity and Acceleration Control for Non-Redundant Manipulators

2000 ◽  
Author(s):  
Yu-Che Chen ◽  
Kevin A. O’Neil
Keyword(s):  
Path Tracking ◽  
Least Square ◽  
Dynamics Simulation ◽  
Control Algorithms ◽  
Redundant Manipulators ◽  
Velocity Control ◽  
Redundant Manipulator ◽  
Singular Configurations ◽  
On Line ◽  
Simulation Results

Abstract Damped Least Square (DLS) method has been widely used as an on-line algorithm for manipulator path tracking near and at singular configurations. Wampler (1986) formulated the framework of DLS method applied to velocity control and addressed the applicability of DLS method to acceleration control. The purpose of this paper is to demonstrate the differences in the joint paths generated by damped velocity and damped acceleration control algorithms in non-redundant manipulators. We examine these joint paths, find the cause of the differences, and demonstrate the features of damped acceleration control in non-redundant manipulator dynamics. Simulation results on a planar 2R and a spatial 6R manipulator moving through and near singular configurations verify the phenomena analyzed.

scholarly journals Sampled-Data-Based Adaptive Group Synchronization of Second-Order Nonlinear Complex Dynamical Networks with Time-Varying Delays

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Bo Liu ◽  
Jiahui Bai ◽  
Yue Zhao ◽  
Chao Liu ◽  
Xuemin Yan ◽  
...  
Keyword(s):  
Adaptive Strategy ◽  
Second Order ◽  
Complex Dynamical Networks ◽  
Time Varying ◽  
Sampled Data ◽  
Dynamical Networks ◽  
Coupling Strengths ◽  
Simulation Results ◽  
Group Synchronization ◽  
The Given

This paper studies the adaptive group synchronization of second-order nonlinear complex dynamical networks with sampled-data and time-varying delays by designing a new adaptive strategy to feedback gains and coupling strengths. According to Lyapunov stability properties, it is shown that the agents of subgroups can converge the given synchronous states, respectively, under some conditions on the sampled period. Moreover, some simulation results are given.

Numerical Simulation by CGM for Moving Force Identification

2012 ◽  
Vol 238 ◽  
pp. 826-829
Author(s):  
Zhen Chen ◽  
Jun Ling Han
Keyword(s):  
Numerical Simulation ◽  
Time Domain ◽  
Bending Moment ◽  
Identification Accuracy ◽  
Time Varying ◽  
Acceptable Solution ◽  
Moving Force ◽  
Ill Posed ◽  
Simulation Results ◽  
The Time Domain

The conjugate gradient method (CGM) is compared with the time domain method (TDM) in the paper. The numerical simulation results show that the CGM have higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-posed problems to some extent when they are used to identify the moving force. When the bending moment responses are used to identify the time-varying loads, the identification accuracy is more obviously improved than the TDM, which is more suitable for the time-varying loads identification.

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