A Self-Tuning Analog Proportional-Integral-Derivative (PID) Controller

Authors:
Varun Aggarwal;Meng Mao;Una-May O'Reilly
Affiliations:
Massachusetts Institute of Technology, USA;Massachusetts Institute of Technology, USA;Massachusetts Institute of Technology, USA
Venue:
AHS '06 Proceedings of the first NASA/ESA conference on Adaptive Hardware and Systems
Year:
2006

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Abstract

We present a platform for implementing low power selftuning analog proportional-integral-derivative controllers. By using a model-free tuning method, the platform overcomes problems typically associated with reconfigurable analog arrays. Unlike a self-tuning digital PID controller, our prototype controller combines the advantages of low power, no quantization noise, high bandwidth and high speed. The prototype hardware uses a commercially available field programmable analog array and Particle Swarm Optimization as the tuning method. We show that a selftuned analog PID controller can outperform a hand-tuned solution and demonstrate adaptability to plant drift.