Application of Immune Algorithm Optimizing PID Parameters in Simulink

Sheng Bo Zhang

doi:10.4028/www.scientific.net/AMM.615.391

Paper Titles

Research on Supervisory Control and Data Acquisition System Based on Stacker
p.370

Sliding Mode Control Based on Novel Nonlinear Sliding Surface for a Class of Time-Varying Delay Systems
p.375

The Kitchen Vehicle Pressure Autocontrol System Based on SC-UWB Technology of Internet Things
p.382

Simulation Research of Switching Power Supply Based on CMAC and PID Compound Control
p.387

Application of Immune Algorithm Optimizing PID Parameters in Simulink
p.391

Research on Triple-Loop Control of BLDCM Based on Fuzzy PID
p.395

Study on Direct Torque Control of Brushless Doubly-Fed Machine Based on Discete Space Vector Modulation
p.402

Design of BP Neural Network Controller for Infrared Seeker Servo System Based on Stribeck Friction Model
p.409

Vehicle Noise Main Control Technology and the Important Parts
p.415

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 615Application of Immune Algorithm Optimizing PID...

Application of Immune Algorithm Optimizing PID Parameters in Simulink

Abstract:

The PID control model of alternating current governor system was established in Simulink and using immune algorithm to optimize PID controller parameters. It takes PID controller parameters as antibody and the optimal solution as antigens,dynamically adjust PID control parameters in the control process through the immune algorithm of memory cells and antibody concentration regulation mechanism of genetic algorithm.. The antibody coding method, diversity evaluation of the solution, immune operation and Optimization method of steps were detailed. The simulation results show that the immune algorithm was fewer iteration times and high efficiency. The optimized control system reduced the overshoot, improved the response speed and improved the system performance which is a kind of effective optimization method to PID controller parameters.

You might also be interested in these eBooks

Automatic Control and Mechatronic Engineering III

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 615)

Pages:

391-394

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.615.391

Citation:

Cite this paper

Online since:

August 2014

Authors:

Sheng Bo Zhang

Keywords:

Antibody, Immune Algorithm, Optimize, PID Controller

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Chen Junghui, Huang Tie. Applying Neural Networks to online Updated PID Controllers for Nonlinear Process Control[J]. Journal of Process Control, 2004, 14(3): 211—230.

DOI: 10.1016/s0959-1524(03)00039-8

Google Scholar

[2] Zhang H．Constrained Multi objective Optimization Immune Algorithm：Convergence and Application[J]．Computers and Mathematics with Applications，2006，52(5)l 791—808.

Google Scholar

[3] Zhang Yishun, Yang hai . Study of fuzzy PID position control to Nc machine tool feed servo system based on genetic algorithm [J]. Industrial instrumentation and automation equipment. 2009, 6. 53-57.

Google Scholar

[4] zhang hong, Huang Xiyue. Multi-objective constraint optimization immune algorithm and application [J]. Journal of pattern recognition and artificial intelligence, 2008 (4) : 452-458.

Google Scholar

[5] wang qiang, Qian Min. The PID design of Improved immune algorithm and application in the speed control system [J]. Electric drive, 2009 Vol. 39, No. 2.: 56-60.

Google Scholar

[6] RuanYi, xu jing. Induction motor control according to stator field-oriented[J]. Journal of electrotechnics. 2003, 18 (2) : 34-37.

Google Scholar