Optimization of flight control system using different optimization techniques against a common set of handling quality criteria

Abstract

Optimization of Flight Control System using different optimization techniques against a common set of Handling Quality Criteria’s has been studied and demonstrated for several flight conditions. Finally these various optimization techniques are compared with each other. The optimization techniques considered are Co-Evolutionary Augmented Lagrangian Method, Genetic Algorithm and Particle Swarm Optimization. These methods are applied to the design of Longitudinal and Lateral Directional Control laws for F-16 Fighter Aircraft. In this report, first we achieved a feasible design space that satisfied the stability and the handling qualities to the best (Level 1 category B) criteria. Finally the controller tuning was accomplished to minimize the performance index using CEALM, GA and PSO. Here we designed the control system which minimizes the performance indexes satisfying the given constraints obtained from Level 1 criteria with constructing Stability and Control Augmented System of F-16 internal loop and outer Autopilot. Here all of the gains are set as the optimization parameters. An important finding of this research is that the optimization techniques used for numerical simulations, yield controllers whose performance and stability characteristics are quiet similar to one another. The study uses MATLAB/Simulink dynamic simulation and analysis software for model building, control law design and subsequent analysis. The performances of the proposed Autopilots and Optimization are compared and analyzed through numerical simulations for three flight conditions.