2012 | OriginalPaper | Buchkapitel
PID Controller Tuning Using Multi-objective Optimization Based on Fused Genetic-Immune Algorithm and Immune Feedback Mechanism
verfasst von : Maryam Khoie, Karim Salahshoor, Ehsan Nouri, Ali Khaki Sedigh
Erschienen in: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, a Genetic-AIS (Artificial Immune System) algorithm is introduced for PID (Proportional-Integral-Derivative) controller tuning using a multi-objective optimization framework. This hybrid Genetic-AIS technique is faster and accurate compared to each individual Genetic or AIS approach. The auto-tuned PID algorithm is then fused in an Immune feedback law based on a nonlinear proportional gain to realize a new PID controller. Immune algorithm presents a promising scheme due to its interesting features such as diversity, distributed computation, adaptation and self monitoring. Accordingly, this leads to a more effective Immune-based tuning than the conventional PID tuning schemes benefiting a multi-objective optimization prospective. Integration of Genetic-AIS algorithm with Immune feedback mechanism results into a robust PID controller which is ultimately evaluated via simulation control test scenarios to demonstrate quick response, good robustness, and satisfactory overshoot and disturbance rejection characteristics.