<p>This paper extends our previous contributions about aircraft system identification to more complex dynamic network identification, corresponding to the novel formation flight module. After reviewing our existed results about open-loop identification, closed-loop identification and cascade system identification, appearing in real aircraft system, the novel formation flight module is described to be the aircraft formation dynamic network system, embodying the communication network and data network simultaneously. To identify each unknown aircraft system within this dynamic network, prediction error method is proposed to identify each flying aircraft, while combining closed-loop system and other communication path. Then, consider some sensor noises existing in dynamic network, instrumental variable method is improved to guarantee the unbiased or consistent estimation performance. Moreover, for the sake of completeness with system identification for control, distributed strategy is applied to design each controller, existing in dynamic network, while giving our own derivations about the combination of system identification and distributed controller design. Finally, a platform about one practical aircraft flight system is exemplified to show our theoretical analysis.</p>

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Aircraft system identification within dynamic network

  • Wang Jianhong,
  • Cao Lei

摘要

This paper extends our previous contributions about aircraft system identification to more complex dynamic network identification, corresponding to the novel formation flight module. After reviewing our existed results about open-loop identification, closed-loop identification and cascade system identification, appearing in real aircraft system, the novel formation flight module is described to be the aircraft formation dynamic network system, embodying the communication network and data network simultaneously. To identify each unknown aircraft system within this dynamic network, prediction error method is proposed to identify each flying aircraft, while combining closed-loop system and other communication path. Then, consider some sensor noises existing in dynamic network, instrumental variable method is improved to guarantee the unbiased or consistent estimation performance. Moreover, for the sake of completeness with system identification for control, distributed strategy is applied to design each controller, existing in dynamic network, while giving our own derivations about the combination of system identification and distributed controller design. Finally, a platform about one practical aircraft flight system is exemplified to show our theoretical analysis.