Abstract
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.
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Khoie, M., Salahshoor, K., Nouri, E., Sedigh, A.K. (2012). PID Controller Tuning Using Multi-objective Optimization Based on Fused Genetic-Immune Algorithm and Immune Feedback Mechanism. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_35
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DOI: https://doi.org/10.1007/978-3-642-25944-9_35
Publisher Name: Springer, Berlin, Heidelberg
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