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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guangxing Tan Zongyuan Mao Youxin Li Yuanlie He |
| Copyright Year | 2006 |
| Description | Author affiliation: Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou (Guangxing Tan; Zongyuan Mao; Youxin Li; Yuanlie He) |
| Abstract | In some uncertain systems, parameters of PID controller are still difficult to tune. The main reason is that it is difficult to solve conflicts between static state performance and dynamic performance, track and restrain disturb, robustness and control performance. To overcome those demerits, a PID parameter optimization algorithm, which used the idea of immune genetic algorithm, was proposed in this paper. This new algorithm used an AB immune network model to simulate interaction between antibodies and to calculate concentration of antibody, and it was able to converge to the optimum parameters fast and efficiently according to the given controlled system. The simulation results show the improvement in convergent speed, global stability and robustness of the PID controller efficiently |
| Starting Page | 3198 |
| Ending Page | 3202 |
| File Size | 249738 |
| Page Count | 5 |
| File Format | |
| ISBN | 1424403324 |
| DOI | 10.1109/WCICA.2006.1712957 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-06-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Three-term control Optimization methods Automatic control Automation Robust control Robust stability Helium Educational institutions Technology management Engineering management parameter optimization artificial immune AB immune network model PID controller |
| Content Type | Text |
| Resource Type | Article |
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