Browse By Repository:

 
 
 
   

Predictive functional control (PFC) for use in autopilot design

Hyreil Anuar, Kasdirin (2006) Predictive functional control (PFC) for use in autopilot design. Masters thesis, University of Sheffield.

[img]
Preview
PDF (71 Pages)
Predictive_functional_control_(PFC)_for_use_in_autopilot_design015_-_Copy.pdf - Submitted Version

Download (3773Kb) | Preview

Abstract

This paper discusses the design and implementation of PFC as a controller for an autopilot missile. Two linear continuous time missile models which are derived from nonlinear model produced by Horton [13] and another from the basic Ballistic Missile [10] are used for the prediction models. The PFC algorithm is developed based on the models. The PFC algorithm developed is seems intuitive and computationally simple as the missile need not to be very complicated as it will explode as it reaches the target.Furthermore, the analysis and issues of the implementation relating linear discrete-time stable and unstable process are being discussed. In addition, PFC tuning parameters play an important part of the autopilot controller. Thus, the result indicated that the PFC control law is built better when choosing the dynamic pole of the missile mode to be the desired time constant, 'I' and small coincidence horizon n1 as performing in single coincidence point. The implementation of PFC on the missiles-scenario is also developed for Model Missile 1 and 2. As a result, some positive results is illustrated and discussed as the both missile followed its reference trajectory during simulation using MATLAB 7.0.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Process control ,Predictive control
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Library > Tesis > FKE
Depositing User: Mohd. Nazir Taib
Date Deposited: 10 Jun 2015 07:35
Last Modified: 19 Jun 2015 07:42
URI: http://eprints.utem.edu.my/id/eprint/14619

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year