Clearance of flight control law based on cultural differential evolution algorithm

Aiming at the slow converge rate in traditional cultural algorithm and lower use efficiency of knowledge about evolutionary information in differential evolution algorithm, a new cultural differential evolution algorithm is proposed. The cultural algorithm is utilized as the framework of the proposed algorithm, in which the evolution in population space consists of mutation, crossover and selection of the differential evolution. In addition, the population space evolution is guided by the belief space knowledge. According to the flying quality specifications, a nonlinear criterion is presented. The proposed algorithm is then applied to evaluate angle of attack limit exceedance criterion, which is current widely used in the aerospace industry. The full authority flight control law of the Aero-Data Model in Research Environment (ADMIRE) is evaluated with uncertainties by the proposed algorithm, which overcomes the limitations of traditional grid-based ones. The simulation results validate that the reliability, computational complexity and efficiency of the proposed algorithm outperform those of the modified differential evolution algorithm, especially in searching for the worst uncertain parameter combinations for the whole flight envelope.