Bee swarm intelligence can be used for aircraft parameter identification

A recent study suggests that the bionic intelligent method proposed by simulating the behavior of honey bees in search of excellent honey sources provides a new technical approach to solve the problem of parameter identification of hypersonic vehicles.

This research paper titled "Online Parameter Identification of Hypersonic Vehicles Based on Artificial Bee Colony Optimization" was published in "Science in China: Information Science", Issue 11, 2012, which gives artificial bee colony intelligence from the perspective of bionics and artificial intelligence. The technical approach to realize the aircraft parameter identification was written by Professor Duan Haibin, the Key Laboratory of Aircraft Control Integration Technology, School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, as the corresponding author.

Hypersonic vehicles are wingless or winged aircraft such as missiles, artillery shells, and aircraft with a flight speed greater than 5 times the speed of sound. They have high reconnaissance efficiency and penetration success rate, and can greatly expand the battlefield space. Due to the complex aerodynamic characteristics of hypersonic vehicles and the use of advanced technologies such as supersonic combustion ramjet engines and airframe / engine integration, hypersonic technology also faces a large number of bottlenecks. Compared with traditional aircraft, hypersonic vehicles have stronger coupling between various state variables, and the nonlinearity of the model is also higher. Moreover, the flying height and Mach number span of hypersonic vehicles are large, the flight environment is very complex, and the aerodynamic characteristics are intense during the flight process. Changes, the above reasons make the establishment of models of hypersonic vehicles and the identification of parameters in the models particularly difficult. Therefore, it is necessary to explore the use of bionic intelligent means to identify the parameters of hypersonic aircraft models.

The innovation of this research lies in the strong coupling, high nonlinearity and complex flight environment of hypersonic vehicles. For the first time, the artificial bee colony intelligence is used to realize the online parameter identification of hypersonic vehicles, and the introduction of bee mining mechanism and chaos search mechanism , So that the bee colony can jump out of the local optimal value (as shown in Figure 1), and did a comparative study with the traditional maximum likelihood method. The research results show that under the condition that the system measurement noise is small, both the maximum likelihood method and the artificial bee colony method can obtain satisfactory identification results. However, under the condition of large measurement noise, the maximum likelihood method is susceptible to interference, which leads to iterative divergence and cannot give identification results; while the artificial bee colony method is less affected by noise and can still obtain results similar to those of small noise. .

The research results are of reference value to solve the problem of aircraft parameter identification in complex space environment. In addition, it has important scientific significance for deepening the research and application of bionic intelligent computing technology.

The research was supported by the National Natural Science Foundation of China (Grant No. 61273054, 60975072).

Source paper:

Li Shuangtian, Duan Haibin. Online parameter identification of hypersonic vehicles based on artificial bee colony optimization. Science in China: Information Science, 2012, 42 (11): 1350-1363 LI ST, DUAN H B. Artificial bee colony approach to online parameters identification for hypersonic vehicle. SCIENTIA YU Informationis, 2012, 42 (11): 1350-1363

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