A sliding mode approach for control and estimation in active aircraft

监测任何减阻方案的有效性，对于向人们灌输对其有效性的信心是至关重要的。主动或被动减阻方案将代表着飞机上的一种“隐藏”技术，因为它们的效果和正常功能将不容易用肉眼看到。在长时间的操作中监测任何流动控制或减阻方案的效率，使飞行员能够更准确地估计所需的燃料储备，并通过指示飞行期间可能出现的需要检查/维护的问题来帮助地勤人员。其目的是利用滑模观测器来监测飞机性能的变化，这可以与总体阻力性能的变化相关联。阻力的变化将被表示为飞机系统中未知(和不可测量)的变化，并将利用保持滑行所必需的等效输出误差注入信号来估计。基于非线性纵向运动方程的非线性观测器的直接发展消除了与线性化产生的近似相关的误差--当考虑到估计总阻力变化1%所需的精度水平时，这些误差似乎是显著的。滑模观测器方案非常适合于处理这样的场景，因为设计过程不限于线性系统表示。将制定的所有不同战略都可以被视为相互独立地工作的监测系统。然后，“中枢神经系统”可以采用更高级别的监测目标，确认真正的减阻，检测传感器故障，并在遇到测量不准确或故障时发出警报。

Monitoring the effectiveness of any drag reduction scheme is vitally important to instil a level of confidence in its effectiveness. The active or passive drag reduction schemes will represent a 'hidden' technology on the aircraft in the sense that their effects and proper functioning will not be readily visible to the naked eye. Monitoring the efficiency of any flow control or drag reduction scheme over long periods of operation allows the pilot to estimate more accurately the required fuel reserve and assists the ground crews by indicating issues requiring inspection/maintenance which may have arisen during a flight. The objective is to utilize sliding mode observers to monitor changes in the performance of the aircraft which can be correlated to changes in the overall drag performance. Changes in drag will be formulated as unknown (and unmeasurable) changes in the aircraft system and will be estimated utilizing the equivalent output error injection signal necessary to maintain sliding. Direct development of nonlinear observers based on the nonlinear longitudinal equations of motion eliminate the errors associated with the approximations arising from linearizing - which appear to be significant when considering the level of accuracy required to estimate 1% changes in the overall drag. Sliding mode observer schemes are ideally suited to cope with such scenarios since the design process is not limited to linear system representations. All the different strategies that will be developed can be viewed as monitoring systems working independently of each other. The 'central nervous system' can then adopt a higher level monitoring objective, confirming genuine drag reduction, detecting sensor faults, and raising alarms when confronted with issues of inaccurate measurements or faults.