基于改进差分进化算法的飞行控制律评估方法
收稿日期: 2012-07-02
修回日期: 2012-08-23
网络出版日期: 2012-09-05
基金资助
国防预研项目(51327020104)
Evaluation Method for Flight Control Law Based on Modified Differential Evolution Algorithm
Received date: 2012-07-02
Revised date: 2012-08-23
Online published: 2012-09-05
Supported by
National Defence Pre-research Foundation (51327020104)
陈云翔 , 李琳 , 李千 , 纪小柠 . 基于改进差分进化算法的飞行控制律评估方法[J]. 航空学报, 2013 , 34(6) : 1261 -1268 . DOI: 10.7527/S1000-6893.2013.0230
An evaluation method for a fight control law based on modified differential evolution (DE) algorithm is provided. A new modified method based on chaos theory (CT) and Gaussian disturbance (GD) is proposed to deal with the problem of slow search and premature convergence in the basic DE algorithm. Compared with the basic DE and other DE methods, experimental simulations show that the proposed method can not only significantly speed up the convergence, but also effectively solve the premature problem. And then the process to proceed the evaluation of the flight control law is put forward. Finally, the new method is applied to the evaluation of a flight control law. Result shows that the new method overcomes the limitations of the traditional evolution method, and can achieve satisfied results both for the whole flight envelope and for all predictable parameter perturbations.
[1] Liu L, Che J, Tang Q, et al. Study on the advanced approaches for clearance of modern flight control law. Flight Dynamics, 2007, 25(1):1-4. (in Chinese) 刘林, 车军, 唐强, 等. 现代飞行控制律评估与确认先进方法研究.飞行力学, 2007, 25(1): 1-4.
[2] Iqbal S. Analysis of flight test manoeuvres using bifurcation analysis methods in support of flight clearance. AIAA Guidance, Navigation, and Control Conference, 2003: 1-16.
[3] Lowenberg M. Aircraft control law clearance analysis using bifurcation and continuation methods. AIAA Guidance, Navigation, and Control Conference, 2003: 1008-1022.
[4] Chriatopher F, Andras V, Samir B, et al. Advanced techniques for clearance of flight control laws. Berlin: Springer-Verlag, 2002: 313-333.
[5] Selier M, Korte U, Fielding C, et al. New analysis techniques for clearance of flight control laws. AIAA Guidance, Navigation and Control Conference Exhibit, 2003, 976-984.
[6] Glover K, Vinnicombe G, Papageorgiou G. Guaranteedmulti-loop stability margins and the gapmetric. The 38th IEEE Conference on Decision and Control, 2000: 4084-4085.
[7] Liu L, Ji D H, Tang Q. v-gap metric and its application to clearance of flight control laws. Acta Aeronautica et Astronautica Sinica, 2007, 28(4): 930-934. (in Chinese) 刘林, 纪多红, 唐强. ν-gap度量及其在飞行控制律评估中的应用. 航空学报, 2007, 28(4): 930-934.
[8] Lv Q X, Liu L, Tang Q. Robust stability clearance of flight control laws in all flight envelope. Flight Dynamics, 2008, 26(5): 32-39. (in Chinese) 吕全喜, 刘林, 唐强. 飞行控制律全包线鲁棒性稳定性评估.飞行力学, 2008, 26(5): 32-39.
[9] Liu L. Advanced verification and clearance technique for modern flight. Beijing: National Defense Industry Press, 2010: 156-157. (in Chinese) 刘林.现代飞机控制系统的评估与确认方法.北京:国防工业出版社, 2010: 156-157.
[10] Wang Y J, Zhang J S. Global optimization by an improved differential evolutionary algorithm. Applied Mathematics and Computation, 2007, 188(1): 669-680.
[11] Noman N, Iba H. Enhancing differential evolution performance with local search for high dimensional function optimization. Proceedings of the 2005 Conference on Genetic and Evolutionary Computation. Washington, D.C.: ACM, 2005: 967-974.
[12] Noman N, Iba H. Accelerating differential evolution using an adaptive local search. IEEE Transactions on Evolutionary Computation, 2008, 12(1):107-125.
[13] Tan Y, Tan G Z, Tu L. Differential evolution algorithm with local search strategy. Computer Engineering and Applications, 2009, 45(7): 56-58. (in Chinese) 谭跃, 谭冠政, 涂立. 具有局部搜索策略的差分进化算法. 计算机工程与应用, 2009, 45(7): 56-58.
[14] Caponetto R, Fortuna L, Fazzino S, et al. Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 2003, 7(3): 289-304.
[15] Sun C F. Differential evolution and its application on the optimal scheduling of electrical power system. Wuhan: Huazhong University of Science and Technology, 2010. (in Chinese) 孙成富. 差分进化算法及其在电力系统调度优化中的应用研究. 武汉:华中科技大学, 2010.
[16] Tian D P. An adaptive genetic algorithm combined with chaos searching. Journal of Shanxi University of Science & Technology, 2008, 6(26): 65-71.
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