PID Parameters Optimization of Pressure and Phear Testing Controller Based on CLPSO Algorithm

Hong Ji Wu; Zhen Qiu Hu

doi:10.4028/www.scientific.net/AMM.88-89.104

Paper Titles

The Prospect of the Modeling Simulation for the Passive Containment Cooling System of the Advanced PWR in China
p.82

Adaptive Control of Uncertain Gun Control System of Tank
p.88

Characteristic Study on the Dynamic Response of Block Based on the EMD Technique of Feature Extraction
p.93

A Measurement Method of the Interoperability of Integrated Systems Based on Process Net
p.99

PID Parameters Optimization of Pressure and Phear Testing Controller Based on CLPSO Algorithm
p.104

Simpler Formulation and Numerical Validation for a Nonlinear High Order Finite Shell Element
p.110

A Novel Feature Extraction Method for Mechanical Part Recognition
p.116

Control of Direct-Drive Compressor Based on Variable Structure Sliding Mode
p.122

A Study on Shift Process Control of AMT for Battery Electric Bus
p.128

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 88-89PID Parameters Optimization of Pressure and Phear...

PID Parameters Optimization of Pressure and Phear Testing Controller Based on CLPSO Algorithm

Abstract:

This paper presents an improved algorithm which is Comprehensive Learning Particle Swarm Optimization(CLPSO).CLPSO utilizes a new learning strategy have achieve the goal to accelerate the convergence of the classical PSO.CLPSO algorithm is effective to optimize PID controller’s parameter.The simulation results show its better performance than traditional ways in the PID parameter optimization of a hydraulic system controller.

You might also be interested in these eBooks

Computer-Aided Design, Manufacturing, Modeling and Simulation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 88-89)

Pages:

104-109

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.88-89.104

Citation:

Cite this paper

Online since:

August 2011

Authors:

Hong Ji Wu, Zhen Qiu Hu

Keywords:

CLPSO Algorithm, Hydraulic System, PID Tunning, Pressure Testing, Shear Testing

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Wang W, Zhang J T, Chai T Y. A survey of advanced PID parameter tuning methods[J]. Acta Automatica Sinica, 2000, 26(3): 347-355.

Google Scholar

[2] Liang J J, Qin A K, Suganthan P N, et . al. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions[J]. IEEE Trans Evol Comput, 2006, 10(3): 281-294.

DOI: 10.1109/tevc.2005.857610

Google Scholar

[3] Kennedy,J., Eberhart, R, C . Particle Swarm Optimization . In: Proc. of IEEE International Conf. on Neural Networks, Pearth, Austrailia, pp, 1924-1948. (2005).

Google Scholar

[4] Liang, J, J, Qin A, K, Suganthan, P, N Bhaskaar, S Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions. IEEE Transactions on Evolutionary Computation 10(3), 281-295(2006).

DOI: 10.1109/tevc.2005.857610

Google Scholar

[5] R H jin, Z H yuan, J P Jun, Y Fan, J J Li, The pattern synthesis of antennas based on a modified PSO algorithm[J]. Chinese Journal of Radio Science, 2006, 21(6): 873-878.

Google Scholar

[6] Turkington D H, Cooke N, Moss P J , et al. Dvelopment of a design procedure for bridges on lead-rubber bearings. Engineering Structures, 1989, 11(1)2-8.

DOI: 10.1016/0141-0296(89)90026-6

Google Scholar

[7] Hu Shousong Automatic Control Theory (Version 4)[M]. Beijing: Science Press, (2001).

Google Scholar

[8] Lin Lin Ou, Yan Ying Gu, Wei Dong Zhang. The optimal PID parameter tuning method bases on gain margin and phase margin[J]. Control theory and applications, 2007，24(5): 837~840.

Google Scholar

[9] Huang Zhonglin. Control System MATLAB Calculation and Simulation(Version 2)[M]. Beijing: National Defence Industry Press，(2004).

Google Scholar

[10] Takahiro S, Kenko U. Gain Scheduling control For Electro-hydraulic Servo System Considering Time-delay Modeling Erro[C]. Proceeding of the 2004. IEEE International, 2004(2): 1709~1716.

DOI: 10.1109/cca.2004.1387623

Google Scholar

[11] Xu Xiaoping, QIAN Fucai, WAN Feng. Novel method of system identification based on modified particle swarm optimization algorithm[J]. Systems Engineering and Electronic, 200e. 30(11): 2231~2236.

Google Scholar