Gray-box acceleration modeling of an electro hydraulic servo shaking table with neural network

2017 ◽  
Author(s):  
Paolo Righettini ◽  
Roberto Strada ◽  
Shirin Valilou ◽  
Ehsan Khademolama
Keyword(s):  
Neural Network ◽  
Shaking Table ◽  
Hydraulic Servo

Delay compensation position tracking control of electro-hydraulic servo systems based on a delay observer

2019 ◽  
Vol 234 (5) ◽  
pp. 622-633
Author(s):  
Xingya Ding ◽  
Gang Shen ◽  
Xiang Li ◽  
Yu Tang
Keyword(s):  
Position Control ◽  
Signal Transmission ◽  
Experimental Results ◽  
Shaking Table ◽  
Feedback Signal ◽  
Delay Compensation ◽  
Servo Systems ◽  
Hybrid Controller ◽  
Hydraulic Servo ◽  
Backstepping Controller

In this article, the position control problem of electro-hydraulic servo systems with feedback signal transmission delay is studied. In order to improve the control accuracy of the system, a hybrid controller which combines a delay observer, a nonlinear disturbance observer and a backstepping controller is proposed. The controller has the characteristics of compensating the delay of signal transmission, restraining the uncertain disturbance of control systems and high control precision. In order to verify the stability and validity of the proposed hybrid controller, a single-degree-of-freedom electro-hydraulic shaking table is used to verify the experimental results. The experimental results show that the proposed controller has better control effects than proportional integral derivative and backstepping controller.

Performance Assessment of Hydraulic Servo System Based on Radial Basis Function Neural Network and Mahalanobis Distance

2015 ◽  
Vol 764-765 ◽  
pp. 613-618
Author(s):  
Zhen Ya Wang ◽  
Chen Lu ◽  
Hong Mei Liu ◽  
Zi Han Chen
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Performance Assessment ◽  
Basis Function ◽  
Mahalanobis Distance ◽  
Rbf Neural Network ◽  
Residual Error ◽  
Servo Systems ◽  
Radial Basis ◽  
Hydraulic Servo

The performance assessment of hydraulic servo systems has attracted an increasing amount of attention in recent years. However, only a few studies have focused on practical approaches in this field. A performance assessment method based on radial basis function (RBF) neural network and Mahalanobis distance (MD) is proposed in this study; the method is quantized by the performance confidence value (CV). An observer model based on RBF neural network is designed to calculate the residual error between the actual and estimated outputs. The root mean square (RMS), peak value, and average absolute value are then extracted as the features of residual error, which serve as the coordinates of the feature points. Lastly, the MD between the most recent feature point and the constructed Mahalanobis space is calculated. The condition of the system is assessed by normalizing MD into a CV. The proposed method is proven to be effective by a simulation model in which leakage faults are injected. Experimental results show that the proposed method can assess the performance of hydraulic servo systems effectively.

Research on the PID Control Strategy in BP Neural Network of Terrain Detector-Milling Cutting Depth System

2014 ◽  
Vol 945-949 ◽  
pp. 1573-1578
Author(s):  
Xiao Feng ◽  
Hao Hu ◽  
Fan Rang Kong ◽  
Shi Qiu ◽  
Ye Sun
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Bp Neural Network ◽  
Pid Control ◽  
Simulation Analysis ◽  
Dynamic Performance ◽  
Effective Control ◽  
Cutting Depth ◽  
Hydraulic Servo

Targeting at the nonlinear, time-varying characteristics of terrain detector-milling cutting depth electro-hydraulic servo system in soil milling collection machines, this paper proposed the PID control menthod in BP neural network of terrain detector - milling cutting depth system and designed PID controller in BP neural network and conducted simulation analysis by programming with Matlab. The results show that, when compared with conventional PID control, BP neural network compounded with PID control would enable the system better dynamic performance and follow-up characteristics, therefore, it is an effective control strategy.

Adaline neural network-based adaptive inverse control for an electro-hydraulic servo system

2011 ◽  
Vol 17 (13) ◽  
pp. 2007-2014 ◽  
Author(s):  
Jianjun Yao ◽  
Xiancheng Wang ◽  
Shenghai Hu ◽  
Wei Fu
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Servo System ◽  
Inverse Model ◽  
Lms Algorithm ◽  
Adaptive Inverse Control ◽  
Inverse Control ◽  
The Neural Network ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

Based on adaptive inverse control theory, combined with neural network, neural network adaptive inverse controller is developed and applied to an electro-hydraulic servo system. The system inverse model identifier is constructed by neural network. The task is accomplished by generating a tracking error between the input command signal and the system response. The weights of the neural network are updated by the error signal in such a way that the error is minimized in the sense of mean square using (LMS) algorithm and the neural network is close to the system inverse model. The above steps make the gain of the serial connection system close to unity, realizing waveform replication function in real-time. To enhance its convergence and robustness, the normalized LMS algorithm is applied. Simulation in which nonlinear dead-zone is considered and experimental results demonstrate that the proposed control scheme is capable of tracking desired signals with high accuracy and it has good real-time performance.

The resonant valley suppression of a hydraulic shaking table by using adaptive spectral line enhancer

2018 ◽  
Vol 232 (10) ◽  
pp. 1379-1388
Author(s):  
Tao Wang ◽  
Jinchun Song
Keyword(s):  
Spectral Line ◽  
Coupling Effect ◽  
Resonance Effect ◽  
Shaking Table ◽  
Resonance Phenomenon ◽  
Resonant System ◽  
Stability Range ◽  
Elastic Load ◽  
Hydraulic Servo ◽  
The Stability

As an electro-hydraulic servo shaking table takes on an elastic load in a vibration test of a 2-mass dynamic system, a mutual coupling effect is exerted between the shaking table and the specimen, which will form a resonant system to weaken the dynamic characteristics of the system. As required by the system bandwidth, the resonant system contains a resonance valley and a resonance peak, and its amplitude commonly surmounts the stability range of the system’s acceleration amplitude. In this article, the resonance phenomenon is analyzed, and the structure and the parameters of the three-state controller are designed on the basis of a pole assignment system. The adaptive spectral line enhancer is adopted to suppress the resonant valley, and the power spectrum is analyzed to experimentally verify that it exerts an anti-resonance effect.

Sign in / Sign up

Export Citation Format

Share Document