|
|
|
| Clearance of Flight Control Law Based on Cultural Differential Evolution Algorithm |
| LI Ai-Jun1,WANG Jing1,LI Jia2,WANG Chang-Qing1 |
1School of Automation,Northwestern Polytechnical University,Xi′an 710072
2Shanghai Aircraft Design and Research Institute,COMAC,Shanghai 200235 |
|
|
|
|
Abstract 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.
|
|
Received: 12 August 2013
|
|
|
|
|
|
[1]Liu L. Advanced Verification and Clearance Techniques for Modern Flight Control Systems. Beijing,China: National Defense Industry Press,2010: 52-58 (in Chinese)(刘 林.现代飞行控制系统的评估与确认方法.北京:国防工业出版社,2010: 52-58)
[2]Chen Y X,Li L,Li Q,et al. Evaluation Method for Flight Control Law Based on Modified Differential Evolution Algorithm. Acta Aeronautica et Astronautica Sinica,2013,34（6）: 1261-1268 (in Chinese)(陈云翔,李 琳,李 千,等.基于改进差分进化算法的飞行控制律评估方法.航空学报,2013,34（6）: 1261-1268)
[3]Fielding C,Varga A,Bennani S,et al. Advanced Techniques for Clearance of Flight Control Laws. Berlin,Germany: Springer Verlag,2002: 434-445
[4]Lu Q X,Zhan Z Y. Method for Clearance of Nonlinear Flight Control Laws Research. Flight Dynamics,2010,28(1): 20-23 (in Chinese) (吕全喜,占正勇.一种非线性飞行控制律评估方法研究.飞行力学,2010,28(1): 20-23)
[5]Meng W Y,Wei C,Tang J. Cultural Algorithm Based on Particle Swarm Optimization for Clearance of Flight Control Law // Proc of the 6th IEEE Conference on Industrial Electronics and Applications. Beijing,China,2011: 418-423
[6]Menon P P,Kim J,Bates D G,et al. Clearance of Nonlinear Flight Control Laws Using Hybrid Evolutionary Optimization. IEEE Trans on Evolutionary Computation,2006,10(6): 689-699
[7]Lu Y L,Zhou J Z,Li Y H,et al. Differential Evolution Based Cultural Algorithm Combined with Chaotic Search and Its Application. Journal of System Simulation,2009,21(16): 5107-5111 (in Chinese) (卢有麟,周建中,李英海,等.混沌差分文化算法及其仿真应用研究.系统仿真学报,2009,21(16): 5107-5111)
[8]Gao L L,Liu H,Li T X. Particle Swarm Based on Cultural Algorithm for Solving Constrained Optimization Problems. Computer Engineering, 2008,34(5): 179-181 (in Chinese) (高丽丽,刘 弘,李同喜.基于文化粒子群算法的约束优化问题求解.计算机工程,2008,34(5): 179-181)
[9]Xue Y. Optimization Theory and Methods. Beijing,China: Beijing Industrial University Press,2004: 221-224 (in Chinese) (薛 毅.最优化原理与方法.北京:北京工业大学出版社,2004: 221-224)
[10]Menon P P,Bates D G,Postlethwaite I. Deterministic Versus Evolutionary Optimization Methods for Nonlinear Robustness Analysis of Flight Control Laws // Proc of the IEEE Congress on Evolutionary Computation. Singapore. Singapore,2007: 1910-1917
[11]Frossell L,Nilsson U. ADMIRE： The Aero Data Model in a Research Environment 4.0. Technical Report,FOI-R-1624-SE. Stockholm,Sweden: Defence Research Agency,2005
[12]Frossell L. Flight Clearance Analysis Using Global Nonlinear Optimization Based Search Algorithms // Proc of the AIAA Guidance Navigation,and Control Conference and Exhibit. Austin,USA,2003. DOI: 10.2514/6.2003-5481 |
|
|
|
2014, Vol. 27 
