Modern air battles are very dynamic and fast, and put extreme pressure on pilots. In some unpredictable situations, like new discovered threats or mission plan deviation because of enemy aircraft, the pilots might need to replan their predefined flight route. This is very difficult, if not impossible, to do since numerous factors affect it. A system that can help the pilots to do such a thing is needed. P revious work in this field has involved methods from artificial intelligence like A*-search. In this master thesis, implementation of a replanning system based on a control theory method, Model Predictive Control (MPC), is examined. Different factors influencing the path, such as terrain and threats, are included in the algorithm. The results presented in this thesis show that MPC solves the problem. As with every method there are some drawbacks and advantages, but as a summary the method is a very promising one and is worth further development. Proposals of future work and different improvements of the algorithms used here are presented in this report as well.

<p>Modern air battles are very dynamic and fast, and put extreme pressure on pilots. In some unpredictable situations, like new discovered threats or mission plan deviation because of enemy aircraft, the pilots might need to replan their predefined flight route. This is very difficult, if not impossible, to do since numerous factors affect it. A system that can help the pilots to do such a thing is needed. P</p><p>revious work in this field has involved methods from artificial intelligence like A*-search. In this master thesis, implementation of a replanning system based on a control theory method, Model Predictive Control (MPC), is examined. Different factors influencing the path, such as terrain and threats, are included in the algorithm. </p><p>The results presented in this thesis show that MPC solves the problem. As with every method there are some drawbacks and advantages, but as a summary the method is a very promising one and is worth further development. </p><p>Proposals of future work and different improvements of the algorithms used here are presented in this report as well.</p>