Computing the Autopilot Control Algorithm Using Predictive Functional Control for Unstable Model

H. Kasdirin, J. Rossiter
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引用次数: 3

Abstract

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.
基于预测函数控制的不稳定模型自动驾驶仪控制算法计算
本文讨论了具有一个或多个不稳定极点的基于模型的预测函数控制(PFC)控制算法的计算发展。采用一种基本的弹道导弹模型[10]作为不稳定模型来制定采用PFC的控制律算法。PFC算法的开发作为控制器计算简单,由于导弹的功能在到达目标时会爆炸,所以并不十分复杂。此外,还讨论了与线性离散不稳定过程相关的分析和实现问题。因此,设计的PFC算法需要找到合适的调谐参数,因为它在自动驾驶仪控制器的设计中起着重要的作用。因此,期望时间常数Ψ和单个重合点的小重合视界n1的调谐表明,在不稳定导弹模式的动态极点上PFC控制律得到了较好的建立。结果表明,利用弹道设定点,在导弹遵循参考弹道的情况下,利用MATLAB 7.0进行了仿真,得到了一些积极的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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