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2009 International Conference of Soft Computing and Pattern Recognition
Computing the Autopilot Control Algorithm Using Predictive Functional Control for Unstable Model
Malacca, Malaysia
December 04-December 07
ISBN: 978-0-7695-3879-2
This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. One basic Ballistic Missile model [10] is used as an unstable model to formulate the control law algorithm using PFC. PFC algorithm development is computationally simple as a controller and it is not very complicated as the function of a missile will explode as it reaches the target. Furthermore, the analysis and issues of the implementation relating linear discrete-time unstable process are also being discussed. Hence, designed PFC algorithm need to find the suitable tuning parameters as its play an important part of the designing the autopilot controller. Thus, the tuning of the desired time constant, Ψ and small coincidence horizon n1 in a single coincidence point shows that the PFC control law is built better in the dynamic pole of the unstable missile mode. As a result, by using a trajectory set-point, some positive results is presented and discussed as the missile follow its reference trajectory via some simulation using MATLAB 7.0.
Index Terms:
Predictive Functional Control (PFC), autopilot design, state-space models
Citation:
H. A. Kasdirin, J. A. Rossiter, "Computing the Autopilot Control Algorithm Using Predictive Functional Control for Unstable Model," socpar, pp.167-171, 2009 International Conference of Soft Computing and Pattern Recognition, 2009
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