Control of Pneumatic Servo System Based on Neural Network PID Algorithm

Qin Hui Gong

doi:10.4028/www.scientific.net/AMM.457-458.1344

Paper Titles

Research on Core Competitiveness of Real Estate Enterprise Based on Factor Analysis and Clustering Analysis
p.1323

Surface Roughness Measurement Analysis
p.1330

Study on Dynamic Phase Correction Method for Improving the Test Accuracy of the Pneumatic Shape Measuring Roll
p.1334

Research of Radar Waveform Based on Pulse Position Jitter and Relative LPI Performance Analysis
p.1338

Control of Pneumatic Servo System Based on Neural Network PID Algorithm
p.1344

The Research on Development Status and Key Technology of Elastic Wave CT
p.1348

A New Method Based on Position Sensitive Detectors to Measure Spatial Angle of Large-Scale Gyroidal
p.1352

The Research of Intelligent Seat Belt Pretension System Based on Active Safety
p.1357

Research on Passivity-Based ADRC of Direct-Drive Wind Power System Back to Back PWM Converter
p.1363

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 457-458Control of Pneumatic Servo System Based on Neural...

Control of Pneumatic Servo System Based on Neural Network PID Algorithm

Abstract:

The pneumatic servo system has characteristics of nonlinear, time-variant, large parameter variations and external disturbances, which is difficult to control. The conventional PID control is not suitable for the variable parameters of the controlled object, external disturbances. In this paper, the neural network controller combined with PID control is used to control the pneumatic servo system, and the structure diagram, algorithm and learning rule of the single neuron adaptive PID controller are put forward. The results show that,compared with the traditional PID control, the controller has significantly improved the control performance of system, Namely, the system has faster computational speed (real-time), stronger robustness and better adaptive ability.

You might also be interested in these eBooks

Frontiers of Mechanical Engineering and Materials Engineering II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 457-458)

Pages:

1344-1347

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.457-458.1344

Citation:

Cite this paper

Online since:

October 2013

Authors:

Qin Hui Gong

Keywords:

Algorithm (GA), Neural Network PID Control, Pneumatic Servo System, Robustness, Single Neuron Adaptive PID Controller

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] T. Kosaki, M. Sano. Adaptive Gain Control of Pneumatic Servo Systems with Disturbance Observers and Fuzzy Logic. Industrial Electronics, Control and Instrumentation, IECON97. 23 International Conference, 1997（3）.

DOI: 10.1109/iecon.1997.668416

Google Scholar

[2] R.B. Van G.M. Bone. Accurate Position Control of a Pneumatic Actuator Using On/Off Solenoid Valves. Macaronics, IEEE/ASME Transaction, 1997(12).

DOI: 10.1109/3516.622972

Google Scholar

[3] J.W. Lee P.H. Chang. Input/Output Linearization Using Tine Delay Control and Time Delay Observer. American Control Conference, 1998(1).

DOI: 10.1109/acc.1998.694683

Google Scholar

[4] Arkan Kayihan,J. Doyle Francis Local Nonlinear Control of a Process Actuator. IFAC. (1999).

Google Scholar

[5] M. Sorli,S. Pastorelli. Performance of a Pneumatic Force Controlling Servo System: Influence of Valves Conductance. Robotics and Automation, IEEE International Conference, 1993(3).

DOI: 10.1016/s0921-8890(99)00093-7

Google Scholar

[6] F.L. Lewis,A. Yessldirek and K. Liu, Multilayer neural-net controller with guaranteed tracking performance[J]. IEEE Trans. Neural Networks, 1996, 7(1): 1-12.

DOI: 10.1109/72.485674

Google Scholar

[7] A.J. Calise, N. Hovakimyanand M. Idan. Adaptive output feedback control of nonlinear systems using neural networks[J]. Autmatic, 2001, 37(8): 1201-1211.

DOI: 10.1016/s0005-1098(01)00070-x

Google Scholar