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The Development of Neural Network Based System Identification ...

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52 CHAPTER 2 LITERATURE REVIEW<br />

wide range <strong>of</strong> environments. Although the implementation <strong>of</strong> NN based direct adaptive<br />

controller is simple, the design and tuning <strong>of</strong> the controllers are difficult, requiring a<br />

retraining <strong>of</strong> the NN controller each time the controller parameter is altered [Norgaard,<br />

2000].<br />

<strong>The</strong> indirect adaptive type controller such as NN based MPC is much more flexible<br />

in implementation where only the model is identified by the NN while the controller<br />

action (MPC) is calculated at each time step. <strong>The</strong> MPC controller with its anticipated<br />

benefits have been employed successfully to control helicopter based UAS and is expected<br />

to work well with the desired control performance. <strong>The</strong> NN based system identification<br />

techniques reviewed in the previous section are suitable to be used to identify the<br />

dynamic plant. Considering the convergence and computational speed issues <strong>of</strong> the NN<br />

based MPC, an approximation based NN-MPC can be used to speed up the computation<br />

speed. <strong>Based</strong> on the findings from the literature, the NN based MPC seems to fit our<br />

common goal to develop a general adaptive flight controller that can be developed with<br />

less time and effort.<br />

2.5 SUMMARY<br />

In this chapter, a brief literature review about the definition, application and classification<br />

<strong>of</strong> the rotorcraft UAS is provided as a basic introduction to the research topic.<br />

An overview <strong>of</strong> various autonomy components that enable the rotorcraft based UAS to<br />

perform autonomous missions is presented. This research project will focus mainly on<br />

the development <strong>of</strong> automatic flight control components since the automatic control<br />

component is the first key component that needs to be addressed in order to enable a<br />

UAS to be autonomous.<br />

A brief literature review on the helicopter dynamics modelling and NN based<br />

system identification is presented. Various factors that influence the NN prediction<br />

and training performance such as the model structure selection and the choices <strong>of</strong><br />

training algorithms are discussed and highlighted. Available literature on the different<br />

AFCS design techniques is explored with special emphasis given to flight control system

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