A Fuzzy Adaptive PID Control Method for Stabilized Tracking System

Abstract

Stabilized tracking platform is one of the most important part of modern tracking system, which can isolate disturbance, keep attitude reference, and rapidly realizes the identification and tracking of maneuvering target through the image equipment. Currently, the common method of capturing tracking object is to select proportional-integral-derivative (PID) controller parameters in view of the zones of the different miss-distance, which therefore exists the problem of optimizing a PID controller. This paper firstly builds a physical model of the tracking system, and then designs an adaptive fuzzy logic controller (FLC) for tracking loop, where a Mamdanis min-max fuzzy reasoning principle is used to adjust controller parameters. The simulation result shows that the proposed method can obviously improve the stabilized tracking platforms performance in the accurate and fast tracking ability rather than conventional controllers in the stabilized tracking platform.