scholarly journals RBF Nonsmooth Control Method for Vibration of Building Structure with Actuator Failure

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Jianhui Wang ◽  
Chunliang Zhang ◽  
Houyao Zhu ◽  
Xiaofang Huang ◽  
Li Zhang
Keyword(s):  
Control Method ◽  
Rbf Neural Network ◽  
Structural Vibration ◽  
Stable Theory ◽  
Control Methods ◽  
Building Structure ◽  
Control Effect ◽  
Actuator Failure ◽  
Lqr Control ◽  
Simulation Results

In order to accommodate the actuator failure, the finite-time stable nonsmooth control method with RBF neural network is used to suppress the structural vibration. The traditional designed control methods neglect influence of actuator failure in structural vibration. By Lyapunov stable theory, the designed control method is demonstrated to suppress the building structural vibration with actuator failure. Finally, there are some examples to numerically simulate the three-layer building structure which is affected by El Centro seismic wave. Control effect of nonsmooth control is compared with no control and LQR control. The simulation results demonstrate that the designed control method is great for vibration of building structure with actuator failure and great antiseismic effect.

scholarly journals Research on Construction Method of Operational Reliability Control Model for Space Manipulator Based on Particle Filter

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xin Gao ◽  
Yifan Wang ◽  
Hanxu Sun ◽  
Qingxuan Jia ◽  
Xiaojian Yang ◽  
...  
Keyword(s):  
Particle Filter ◽  
Control Method ◽  
Operational Reliability ◽  
Control Model ◽  
Control Methods ◽  
Space Manipulator ◽  
Performance Function ◽  
Model Based ◽  
Simulation Results ◽  
A Performance

The operational reliability of the space manipulator is closely related to the control method. However the existing control methods seldom consider the operational reliability from the system level. A method to construct the operational reliability system control model based on particle filter for the space manipulator is presented in this paper. Firstly, the definition of operational reliability and the degree of operational reliability are given and the state space equations of the control system are established as well. Secondly, based on the particle filter algorithm, a method to estimate the distribution of the end position error and calculate the degree of operational reliability with any form of noise distribution in real time is established. Furthermore, a performance model based on quality loss theory is built and a performance function is obtained to evaluate the quality of the control process. The adjustment value of the end position of the space manipulator can be calculated by using the performance function. Finally, a large number of simulation results show that the control method proposed in this paper can improve the task success rate effectively compared to the simulation results using traditional control methods and control methods based on Bayesian estimation.

Comparative Study on Control Methods for Air Conditioning of Industrial Paint Booths

2019 ◽  
Vol 11 (11) ◽  
pp. 1053-1059
Author(s):  
Murat Ayaz ◽  
Volkan Aygül ◽  
Ferhat Düzenli˙ ◽  
Erkutay Tasdemi˙rci˙
Keyword(s):  
Adaptive Control ◽  
Automotive Industry ◽  
Air Conditioning ◽  
Control Method ◽  
Ventilation System ◽  
Hvac Systems ◽  
Control Methods ◽  
Control Applications ◽  
Time Simulation ◽  
Simulation Results

It is of great importance that each product in industrial production facilities is to be produced in the same quality and standard. Especially in the automotive industry, the painting process needs to be done under certain environmental conditions according to the paint properties used. Therefore, the temperature, humidity and air quality values of the paint booth are very important for a quality painting operation. In this study, adaptive control has been proposed to control of one-zone heating-ventilation system for the paint booths. The system has been modelled by using the Matlab/Simulink. Performance of the proposed control method has been compared with conventional control methods such as On/Off, PID, fuzzy logic in terms of accuracy, efficiency and response time. Simulation results show that the proposed adaptive control is effective in the Heating, Ventilating, and Air Conditioning (HVAC) systems temperature control applications. In addition, energy efficiency in HVAC systems has been provided with the proposed control model. Furthermore, thermal analysis of the system has been done to corroborate simulation results.

DC/AC Converter Based on Buck Regulator

2013 ◽  
Vol 392 ◽  
pp. 435-438
Author(s):  
Rong Chen ◽  
Jia Sheng Zhang
Keyword(s):  
Closed Loop ◽  
Control Method ◽  
Open Loop ◽  
Control Effect ◽  
Integral Control ◽  
Line Frequency ◽  
Working Principle ◽  
Simulation Results ◽  
Proportional Integral Control ◽  
Differential Control

The introduction of DC/AC converter based on buck regulator is firstly shown, and the analysis of the converters working principle is taken. The control method applied for DC/AC converter based on buck regulator is studied also. The control effect of the open-loop proportional-differential control and closed-loop proportional-integral control are compared by using PSIM software. The parameters adopted in the realistic simulation, waveforms such as voltage of modulation reference and load were given. The simulation results proved that adopting the DC/AC converter could achieve a good performance and can gain a line frequency as 50Hz and the correctness of theoretical analysis.

scholarly journals Semiactive Nonsmooth Control for Building Structure with Deep Learning

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Qing Wang ◽  
Jianhui Wang ◽  
Xiaofang Huang ◽  
Li Zhang
Keyword(s):  
Deep Learning ◽  
Control Algorithm ◽  
Closed Loop ◽  
Passive Control ◽  
Harmful Effect ◽  
Structural Vibration ◽  
Stable Theory ◽  
Seismic Action ◽  
Building Structure ◽  
Closed Loop System

Aiming at suppressing harmful effect for building structure by surface motion, semiactive nonsmooth control algorithm with Deep Learning is proposed. By finite-time stable theory, the building structure closed-loop system’s stability is discussed under the proposed control algorithm. It is found that the building structure closed-loop system is stable. Then the proposed control algorithm is applied on controlling the building structural vibration. The seismic action is chosen as El Centro seismic wave. Dynamic characteristics have comparative analysis between semiactive nonsmooth control and passive control in two simulation examples. They demonstrate that the designed control algorithm has great robustness and anti-interference. The proposed control algorithm is more effective than passive control in suppressing structural vibration.

RBF Neural Network in the Application of Synthetic Tower Temperature Decoupling Control Research

2013 ◽  
Vol 380-384 ◽  
pp. 491-494
Author(s):  
Zhe Zhang ◽  
Li Jun Hao ◽  
Bing Ma
Keyword(s):  
Neural Network ◽  
Production Control ◽  
Control Method ◽  
Rbf Neural Network ◽  
Decoupling Control ◽  
Economic Returns ◽  
Chemical Production ◽  
Control Effect ◽  
Control Research ◽  
Coupling Characteristics

The chemical production is vital to the development of our country.It is greatly significant to improve the ammonia synthesis production control project and to increase the economic returns. In allusion to a controlled object with coupling characteristics,in this paper RBF neural network decoupling controller is designed to realize the decoupling control of the synthetic tower temperature. Through the comparison of the simulation test results, the scheme shows that it has a better control effect than the conventional PID decoupling control method, so, if the scheme could be used in the actual chemical production process, it shall have a certain value in use.

The Application of PID Based on Optimized RBF in Thickness Control of Strip Steel

2012 ◽  
Vol 466-467 ◽  
pp. 52-56
Author(s):  
Yu Zhen Yu ◽  
Xin Yi Ren ◽  
Chun Yan Deng ◽  
Xiao Hui Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Pid Controller ◽  
Control Method ◽  
Rbf Neural Network ◽  
Pso Algorithm ◽  
Strip Thickness ◽  
Control Effect ◽  
Thickness Control

The strip thickness control system is difficult to establish an accurate mathematical model, and traditional PID control strategy has a poor adaptive ability, so the effect of control is always not satisfying. According to the problems above, a new control strategy of self-tuning PID controller based on RBF neural network whose parameters are optimized by PSO algorithm is proposed in the paper. The control method integrates advantages of RBF neural network as well as PID controller and good global search capability of PSO algorithm. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in strip thickness control system that proved the correctness and effectiveness of the control method.

scholarly journals Control of hybrid electromagnetic bearing and elastic foil gas bearing under deep learning

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243107
Author(s):  
Xiangxi Du ◽  
Yanhua Sun
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Control Method ◽  
Rbf Neural Network ◽  
Parameter Tuning ◽  
Network Control ◽  
Control Effect ◽  
Hybrid Bearing ◽  
Gas Bearing ◽  
Bearing System

The hybrid electromagnetic and elastic foil gas bearing is explored based on the radial basis function (RBF) neural network in this study so as to improve its stabilization in work. The related principles and structure of hybrid electromagnetic and elastic foil gas bearings is introduced firstly. Then, the proportional, integral, and derivative (PID) bearing controller is introduced and improved into two controllers: IPD and CPID. The controllers and hybrid bearing system are controlled based on the RBF neural network based on deep learning. The characteristics of the hybrid bearing system are explored at the end of this study, and the control simulation research is developed based on the Simulink simulation platform. The effects of the PID, IPD, and CIPD controllers based on the RBF neural network are compared, and they are also compared based on the traditional particle swarm optimization (PSO). The results show that the thickness, spread angle, and rotation speed of the elastic foil have great impacts on the bearing system. The proposed CIPD bearing control method based on RBF neural network has the shortest response time and the best control effect. The controller parameter tuning optimization starts to converge after one generation, which is the fastest iteration. It proves that RBF neural network control based on deep learning has high feasibility in hybrid bearing system. Therefore, the results provide an important reference for the application of deep learning in rotating machinery.

Double Carrier Pulse width Modulation Control for a Quasi Impedance Source Inverter

2011 ◽  
Vol 29 (1) ◽  
pp. 143-146
Author(s):  
Amin Akrami ◽  
Mohsen Gitizadeh ◽  
Majid Nayeripour ◽  
Mohammad Ghaderi
Keyword(s):  
Pulse Width ◽  
Pulse Width Modulation ◽  
Control Method ◽  
Control Methods ◽  
Control Simulation ◽  
Simulation Results ◽  
Modulation Control

Double Carrier Pulse width Modulation Control for a Quasi Impedance Source Inverter The quasi-Z-source inverter (QZSI) is similar to the ZSI. The QZSI has been developed which feature several improvements and no disadvantages when compared to the ZSI. Also Double carrier pulse width modulation control is a new control method for controlling the ZSI and it has a lot of benefit if to compare with other traditional control methods. This paper improved properties of the QZSI by using the double carrier pulse width modulation control. Simulation results will be presented to demonstrate the new features.

scholarly journals Application of Fuzzy Pushdown Automaton on Prediction of Quality Control for Spinning Yarn

2021 ◽  
Vol 50 (1) ◽  
pp. 76-88
Author(s):  
QingE Wu ◽  
Xing Wang ◽  
Zhiwu Chen ◽  
Hu Chen ◽  
Dong Sun ◽  
...  
Keyword(s):  
Quality Control ◽  
Control Method ◽  
Control Design ◽  
Control Methods ◽  
Average Precision ◽  
Pushdown Automaton ◽  
Control Precision ◽  
Design Structure ◽  
Simulation Results ◽  
And Control

In order to perform better recognition, tracking and control for fuzzy and uncertain thing, this paper will design a suitable fuzzy pushdown automaton (FPDA) control method to solve the problem. Firstly, the control design structure of FPDA and the decision reasoning rules in control are given. Secondly, the application of FPDA in prediction of quality control for spinning yarn is discussed in the practical problem. Finally, the comparison of FPDA and other control methods on the target control is given. The simulation results show that the control speed and the average precision of designed FPDA are faster by12ms and higher by 4.98% than that of traditional method, which its control precision is 96.87%.

Based on NERGA a Novel Decentralized PID for Non-Square System

2011 ◽  
Vol 179-180 ◽  
pp. 1143-1149 ◽  
Author(s):  
Ling Quan ◽  
Qi Bing Jin ◽  
Xue Wei Wang
Keyword(s):  
Pid Control ◽  
Time Delays ◽  
Control Method ◽  
Multivariable Control ◽  
Pid Controllers ◽  
Control Methods ◽  
Chemical Production ◽  
Input And Output ◽  
The Matrix ◽  
Simulation Results

Multivariable non-square system with time delays often arises in the chemical production process. Owing to the matrix that is adopted to describe non-square system is not square, many classical multivariable control methods can be hardly applied in such system. In this paper, based on Non-square effective relative gain (NERGA) a novel decentralized PID control method is proposed. The input and output loops of the non-square system are paired though NERGA firstly, and then strong robust decentralized multivariable proportional-integral-differential (PID) controllers are designed individually based on the squared models. Finally, Simulation study was carried out for three inputs and two outputs system, the simulation results can demonstrate the effectiveness of the proposed method.

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