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The cohesiveness of autonomous cooperative system is the basis of achieving the effective communication and cooperation among the multiple vehicles. Therefore, the biosphere mechanism of queen mandibular pheromone is used for reference in this paper, to abstract the macro motion characteristic of multiple unmanned aerial vehicles autonomous cooperative tracking system. Then, some Lyapunov functions are constructed to analyze the stability of this system, thus obtaining its judgment criterion of stability. Finally, the simulation is given to verify the effectiveness of the proposed stable mechanism. The results show that the proposed stable mechanism not only can ensure the stability of autonomous cooperative system, but also can control the scale of this system effectively by adapting some relevant control parameters.
[1] No T S, Kim Y, Tahk M J, Jeon G E 2011 Aerosp. Sci. Technol. 15 431
[2] Pablo L, Seng K G, Eva B P, Gonzalo P 2014 Inform. Sci. 282 92
[3] Manathara J G, Sujit P B, Beard R W 2011 J. Intellig. Robot. Syst. 62 125
[4] Sun T Y, Huo C L, Tsai S J, Yu Y H, Liu C C 2011 Expert Syst. Appl. 38 10036
[5] Zhang B C, Liu W Q, Mao Z L 2014 Automatica 50 809
[6] Stipanovic D M, Inalhan G, Teo R, Tomlin C J 2004 Automatica 40 1286
[7] Giulietti F, Innocenti M, Napolitano M, Pollini L 2005 Aerosp. Sci. Technol. 9 68
[8] Paul T, Krogstad T, Gravdahl J 2008 Simul. Modell. Practice Theory 16 1453
[9] Sun Y G 2013 Nonlinear Analysis: Real World Applications 14 1075
[10] Das S, Goswami D, Mukherjee S 2014 Engin. Appl. Artific. Intellig. 30 189
[11] Monshizadeh N, Trentelman H L 2013 Syst. Control Lett. 62 1
[12] Goodwine B, Antsaklis P 2013 Automatica 49 3158
[13] Ji L H, Liao X F 2013 Chin. Phys. B 22 040203
[14] Xie Y Y, Wang Y, Ma Z J 2014 Acta Phys. Sin. 63 040202 (in Chinese) [谢媛艳, 王毅, 马忠军 2014 物理学报 63 040202]
[15] Su H S, Wang X F 2009 IEEE Trans. Autom. Control 54 293
[16] Xu X L, Chen S Y, Huang W, Gao L X 2013 Neurocomputing 118 334
[17] Hu H X, Liu A D, Xuan Q, Yu L, Xie G M 2013 Syst. Control Lett. 62 1125
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[1] No T S, Kim Y, Tahk M J, Jeon G E 2011 Aerosp. Sci. Technol. 15 431
[2] Pablo L, Seng K G, Eva B P, Gonzalo P 2014 Inform. Sci. 282 92
[3] Manathara J G, Sujit P B, Beard R W 2011 J. Intellig. Robot. Syst. 62 125
[4] Sun T Y, Huo C L, Tsai S J, Yu Y H, Liu C C 2011 Expert Syst. Appl. 38 10036
[5] Zhang B C, Liu W Q, Mao Z L 2014 Automatica 50 809
[6] Stipanovic D M, Inalhan G, Teo R, Tomlin C J 2004 Automatica 40 1286
[7] Giulietti F, Innocenti M, Napolitano M, Pollini L 2005 Aerosp. Sci. Technol. 9 68
[8] Paul T, Krogstad T, Gravdahl J 2008 Simul. Modell. Practice Theory 16 1453
[9] Sun Y G 2013 Nonlinear Analysis: Real World Applications 14 1075
[10] Das S, Goswami D, Mukherjee S 2014 Engin. Appl. Artific. Intellig. 30 189
[11] Monshizadeh N, Trentelman H L 2013 Syst. Control Lett. 62 1
[12] Goodwine B, Antsaklis P 2013 Automatica 49 3158
[13] Ji L H, Liao X F 2013 Chin. Phys. B 22 040203
[14] Xie Y Y, Wang Y, Ma Z J 2014 Acta Phys. Sin. 63 040202 (in Chinese) [谢媛艳, 王毅, 马忠军 2014 物理学报 63 040202]
[15] Su H S, Wang X F 2009 IEEE Trans. Autom. Control 54 293
[16] Xu X L, Chen S Y, Huang W, Gao L X 2013 Neurocomputing 118 334
[17] Hu H X, Liu A D, Xuan Q, Yu L, Xie G M 2013 Syst. Control Lett. 62 1125
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