Ближневосточный технический университет (Middle East Technical University, Ankara), 2006. – 167 с. (на англ. яз.). Специальность: Электроника (Electrical and electronics engineering).In this thesis, an intelligent controller for gun and/or sight stabilization of turret subsystems is developed using artificial neural networks. A classical proportional, integral and derivative (PID) controller equipped with a non-linear unbalance compensation algorithm is used as the low-level controller. The gains of this PID controller are tuned using a multilayered back-propagation neural network. These gains are modeled as a function of the error between the command and feedback signals and this model is generated by the function fitting property of neural networks as an estimate. The network is called as the Neural PID Tuner and it takes the current and previous errors as inputs and outputs the PID gains of the controller.Content:
Introduction.
Literature survey.
Proposed controller architecture.
Simulation environment and hardware experimental setup.
Results and discussions.
Sensitivity and performance analysis.
Conclusion and future work.
