The Stability of Discrete Impulsive Control System

2006 ◽  
Author(s):  
Liu Feng ◽  
Guan Zhihong ◽  
O Wang Hua
Keyword(s):  
Control System ◽  
Impulsive Control ◽  
The Stability

scholarly journals Stability Analysis for Nonlinear Impulsive Control System with Uncertainty Factors

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zemin Ren ◽  
Shiping Wen ◽  
Qingyu Li ◽  
Yuming Feng ◽  
Ning Tang
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Parameter Uncertainty ◽  
Impulsive Control ◽  
Schwarz Inequality ◽  
Sufficient Condition ◽  
Uncertainty Factors ◽  
Numerical Example ◽  
Gain Error ◽  
The Stability

Considering the limitation of machine and technology, we study the stability for nonlinear impulsive control system with some uncertainty factors, such as the bounded gain error and the parameter uncertainty. A new sufficient condition for this system is established based on the generalized Cauchy–Schwarz inequality in this paper. Compared with some existing results, the proposed method is more practically applicable. The effectiveness of the proposed method is shown by a numerical example.

Investigation of the stability of periodic motions in a nonlinear automatic control system based on the fast fourier transform

2003 ◽  
Vol 3 ◽  
pp. 297-307
Author(s):  
V.V. Denisov
Keyword(s):  
Fourier Transform ◽  
Control System ◽  
Automatic Control ◽  
Fast Fourier Transform ◽  
Automatic Control System ◽  
Resonance Phenomenon ◽  
Periodic Motions ◽  
Multiply Connected ◽  
Non Linear ◽  
The Stability

An approach to the study of the stability of non-linear multiply connected systems of automatic control by means of a fast Fourier transform and the resonance phenomenon is considered.

scholarly journals A Unified Control Strategy of Distributed Generation for Grid-Connected and Islanded Operation Conditions Using an Artificial Neural Network

2021 ◽  
Vol 13 (11) ◽  
pp. 6388
Author(s):  
Karim M. El-Sharawy ◽  
Hatem Y. Diab ◽  
Mahmoud O. Abdelsalam ◽  
Mostafa I. Marei
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Control System ◽  
Distributed Generation ◽  
Control Strategy ◽  
Current Control ◽  
Operating Conditions ◽  
Pi Controllers ◽  
Artificial Neural ◽  
The Stability

This article presents a control strategy that enables both islanded and grid-tied operations of a three-phase inverter in distributed generation. This distributed generation (DG) is based on a dramatically evolved direct current (DC) source. A unified control strategy is introduced to operate the interface in either the isolated or grid-connected modes. The proposed control system is based on the instantaneous tracking of the active power flow in order to achieve current control in the grid-connected mode and retain the stability of the frequency using phase-locked loop (PLL) circuits at the point of common coupling (PCC), in addition to managing the reactive power supplied to the grid. On the other side, the proposed control system is also based on the instantaneous tracking of the voltage to achieve the voltage control in the standalone mode and retain the stability of the frequency by using another circuit including a special equation (wt = 2πft, f = 50 Hz). This utilization provides the ability to obtain voltage stability across the critical load. One benefit of the proposed control strategy is that the design of the controller remains unconverted for other operating conditions. The simulation results are added to evaluate the performance of the proposed control technology using a different method; the first method used basic proportional integration (PI) controllers, and the second method used adaptive proportional integration (PI) controllers, i.e., an Artificial Neural Network (ANN).

The Correlation between Time and Frequency Dynamic Performance of Control System

2014 ◽  
Vol 628 ◽  
pp. 186-189
Author(s):  
Meng Xiong Zeng ◽  
Jin Feng Zhao ◽  
Wen Ouyang
Keyword(s):  
Control System ◽  
Performance Index ◽  
Dynamic Performance ◽  
Frequency Domain Analysis ◽  
Practical Significance ◽  
Order System ◽  
Time Frequency ◽  
Performance Indexes ◽  
Quantitative Performance ◽  
The Stability

The control system performance requirement was divided into three parts. They were the stability, rapidity and accuracy. The time-frequency domain analysis in the requirements of three performance were measured through quantitative performance index. The mutual restriction of time-frequency performance and system characteristic parameters of normal second order was discussed. The correlation of system time-frequency performance index was established. The relationship between time-frequency performance indexes in standard two order system was extended to higher order system. The mutually constraining and time-frequency correlation between each performance index was obtained by analysis and calculation. The work had been done above had practical significance to reflect the system dynamic performance in different analytical domains.

Design of Hydraulic Descaling Computer Control System

2014 ◽  
Vol 608-609 ◽  
pp. 19-22
Author(s):  
Ping Xu ◽  
Jian Gang Yi
Keyword(s):  
Control System ◽  
Stability Problem ◽  
Computer Control ◽  
Control Methods ◽  
Computer Control System ◽  
Control Software ◽  
Pressure Water ◽  
Working Principle ◽  
The Stability

Hydraulic descaling system is the key device to ensure the surface quality of billet. However, traditional control methods lead to the stability problem in hydraulic descaling system. To solve the problem, the construction of the hydraulic descaling computer control system is studied, the working principle of the system is analyzed, and the high pressure water bench of hydraulic descaling is designed. Based on it, the corresponding computer control software is developed. The application shows that the designed system is stable in practice, which is helpful for enterprise production.

Design of an Observer-Based Repetitive Control System to Reject Periodic Disturbance

2016 ◽  
Vol 25 (06) ◽  
pp. 1650061 ◽  
Author(s):  
Zhen Shao ◽  
Zhengrong Xiang
Keyword(s):  
Control System ◽  
Disturbance Rejection ◽  
Lyapunov Functional ◽  
Repetitive Control ◽  
Sufficient Condition ◽  
Two Dimensional ◽  
Periodic Disturbance ◽  
Repetitive Learning ◽  
The Stability ◽  
2D Model

This paper concerns the design of an observer-based repetitive control system (RCS) to improve the periodic disturbance rejection performance. The periodic disturbance is estimated by a repetitive learning based estimator (RLE) and rejected by incorporation of the estimation into a repetitive control (RC) input. Firstly, the configuration of the observer-based RCS with the RLE is described. Then, a continuous–discrete two-dimensional (2D) model is built to describe the RCS. By choosing an appropriate Lyapunov functional, a sufficient condition is proposed to guarantee the stability of the RCS. Finally, a numerical example is given to verify the effectiveness of the proposed method.

Globalized Dual Heuristic Dynamic Programming in Control of Robotic Manipulator

2016 ◽  
Vol 817 ◽  
pp. 150-161 ◽  
Author(s):  
Marcin Szuster ◽  
Piotr Gierlak
Keyword(s):  
Neural Networks ◽  
Dynamic Programming ◽  
Control System ◽  
Degrees Of Freedom ◽  
Dynamic Programming Algorithm ◽  
Robotic Manipulator ◽  
Iteration Step ◽  
Programming Algorithm ◽  
Heuristic Dynamic Programming ◽  
The Stability

The article focuses on the implementation of the globalized dual-heuristic dynamic programming algorithm in the discrete tracking control system of the three degrees of freedom robotic manipulator. The globalized dual-heuristic dynamic programming algorithm is included in the approximate dynamic programming algorithms family, that bases on the Bellman’s dynamic programming idea. These algorithms generally consist of the actor and the critic structures realized in a form of artificial neural networks. Moreover, the control system includes the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis, which was realized using the Lyapunov stability theorem. The control system works on-line and the neural networks’ weight adaptation process is realized in every iteration step. A series of computer simulations was realized in Matlab/Simulink software to confirm performance of the control system.

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