<p>Before a new flight control system is released for flight, a huge number of simulations are evaluated to find weaknesses of the system. This process is called flight clearance. Flight clearance is a very important but time consuming process. There is a need of better flight clearance methods and one of the most promising methods is the use of optimization. In this thesis the flight clearance of a simulation model of JAS 39 Gripen is examined. Two flight clearance algorithms using two different optimization methods are evaluated and compared to each other and to a traditional flight clearance method.</p><p>In this thesis the flight clearance process is separated into three cases: search for the worst flight condition, search for the worst manoeuvre and search for the worst flight condition including parameter uncertainties. For all cases the optimization algorithms find a more dangerous case than the traditional method. In the search for worst flight condition, both with and without uncertainties, the optimization algorithms are to prefer to the traditional method with respect to the clearance results and the number of objective function calls. The search for the worst manoeuvre is a much more complex problem. Even as the algorithms find more dangerous manoeuvres than the traditional method, it is not certain that they find the worst manoeuvres. If not other methods should be used the problem has to be rephrased. For example other optimization variables or a few linearizations of the optimization problem could reduce the complexity.</p><p>The overall impression is that the need of information and problem characteristics define which method that is most suitable to use. The information required must be weighed against the cost of objective function calls. Compared to the traditional method, the optimization methods used in this thesis give extended information about the problems examined and are better to locate the worst case.</p>

Before a new flight control system is released for flight, a huge number of simulations are evaluated to find weaknesses of the system. This process is called flight clearance. Flight clearance is a very important but time consuming process. There is a need of better flight clearance methods and one of the most promising methods is the use of optimization. In this thesis the flight clearance of a simulation model of JAS 39 Gripen is examined. Two flight clearance algorithms using two different optimization methods are evaluated and compared to each other and to a traditional flight clearance method. In this thesis the flight clearance process is separated into three cases: search for the worst flight condition, search for the worst manoeuvre and search for the worst flight condition including parameter uncertainties. For all cases the optimization algorithms find a more dangerous case than the traditional method. In the search for worst flight condition, both with and without uncertainties, the optimization algorithms are to prefer to the traditional method with respect to the clearance results and the number of objective function calls. The search for the worst manoeuvre is a much more complex problem. Even as the algorithms find more dangerous manoeuvres than the traditional method, it is not certain that they find the worst manoeuvres. If not other methods should be used the problem has to be rephrased. For example other optimization variables or a few linearizations of the optimization problem could reduce the complexity. The overall impression is that the need of information and problem characteristics define which method that is most suitable to use. The information required must be weighed against the cost of objective function calls. Compared to the traditional method, the optimization methods used in this thesis give extended information about the problems examined and are better to locate the worst case.