<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.

<p>Flight Control Systems are often designed in linearization points over a flight envelope and it must be proven to clearance authorities that the system works for different parameter variations and failures all over this envelope. </p><p>In this thesis µ-analysis is tried as a complement for linear analysis in the frequency plane. Using this method stability can be guaranteed for all static parameter combinations modelled and linear criteria such as phase and gain margins and most unstable eigenvalue can be included in the analysis. A way of including bounds on the parameter variations using parameter dependent Lyapunov functions is also tried. </p><p>To perform µ-analysis the system must be described as a Linear Fractional Transformation (LFT). This is a way of reformulating a parameter dependent system description as an interconnection of a nominal linear time invariant system and a structured parameter block. </p><p>A linear and a rational approximation of the system are used to make LFTs. These methods are compared. Four algorithms for calculation of the upper and lower bounds of µ are evaluated. The methods are tried on VEGAS, a SAAB research aircraft model. </p><p>µ-analysis works quite well for linear clearance. The rational approximation LFT gives best results and can be cleared for the criteria mentioned above. A combination of the algorithms is used for best results. When the Lyapunov based method is used the size of the problem grows quite fast and, due to numerical problems, stability can only be guaranteed for a reduced model.</p>

Flight Control Systems are often designed in linearization points over a flight envelope and it must be proven to clearance authorities that the system works for different parameter variations and failures all over this envelope. In this thesis µ-analysis is tried as a complement for linear analysis in the frequency plane. Using this method stability can be guaranteed for all static parameter combinations modelled and linear criteria such as phase and gain margins and most unstable eigenvalue can be included in the analysis. A way of including bounds on the parameter variations using parameter dependent Lyapunov functions is also tried. To perform µ-analysis the system must be described as a Linear Fractional Transformation (LFT). This is a way of reformulating a parameter dependent system description as an interconnection of a nominal linear time invariant system and a structured parameter block. A linear and a rational approximation of the system are used to make LFTs. These methods are compared. Four algorithms for calculation of the upper and lower bounds of µ are evaluated. The methods are tried on VEGAS, a SAAB research aircraft model. µ-analysis works quite well for linear clearance. The rational approximation LFT gives best results and can be cleared for the criteria mentioned above. A combination of the algorithms is used for best results. When the Lyapunov based method is used the size of the problem grows quite fast and, due to numerical problems, stability can only be guaranteed for a reduced model.