The aircraft integrated control system reconfiguration laws under failures of actuators, calculated disregarding physical constraints on control surfaces saturation, can lead to a complete loss of aircraft controllability and stability. Despite the large number of scientific publications in this field, practical systematic results have been obtained only for SISO (single input – single output) systems. Problems of the convergence of iterative algorithms restricting the set of admissible solutions and the conservatism of the reconfiguration laws designed using weight matrices do not allow solving this problem in general. For complex MIMO (multi input – multi output) systems there is still no widely accepted universal approach. In this work, control surfaces constraints are regarded in terms of the power of reconfiguration control. It is shown that by slight modification of pseudoinverse (optimal) solution it is possible to obtain approximate pseudoinverse (suboptimal) solutions with priory known minimum power (compensation matrix norm) and error (residual matrix norm) of the reconfiguration for a given degree of approximation. This allows for a multistep consistent reduction in power and increasing in error of reconfiguration, until an acceptable solution is obtained. By providing the greater reconfiguration error at each step we have additional freedom in reducing the reconfiguration power. This leads to a decrease in the amplitude of the deviations of the control surfaces, to which the signals from the failed control channels are redistributed. The simulation example of the aircraft integrated control system reconfiguration under the stabilizer’s actuator failure is presented. It is shown that the pseudoinverse reconfiguration problem solution leads to the significant ailerons’ constraints violation and the loss of aircraft controllability. Regarding control constraints solution reduces several times the deviation of the control surfaces and provides an effective problem solution in the permissible power and error reconfiguration range.

The control system sensors failures can cause the aircraft stability and controllability deterioration. Such failures fast and reliable inflight detection and localization allows minimization their consequences and prevention of an accident. Direct application of traditional parametric methods for sensors health monitoring with the use of their mathematical models is impossible due to the lack of information about the real inputs on their sensitive elements. This leads to the need for the problem of aircraft flight dynamics modeling with a high level of uncertainties to be solved, which complicates the application of functional test methods and determines the necessity of excessive sensors hardware redundancy. Widely known nonparametric methods either require a prior knowledge base, preliminary training, or long-term tuning on a large real flight data volume, or have low selective sensitivity for the failed sensors reliable localization. This paper expands the application of the well-known nonparametric failure detection criterion, based on the analysis of the linear dependence of the input-output data Hankel matrix columns and solution of the sensor failures localizing problem. Necessary and sufficient solvability conditions are given, the structure and the criterion values are determined in an analytical form before and after the failures occurrence. The proposed method does not require functional or hardware redundancy, prior information about the parameters of mathematical models and their stability, identification, observation, or prediction problems solution. The efficiency of the method is shown on the Boeing 747–100/200 longitudinal model example. Fast tuning, fast response and selective sensitivity of the developed algorithms are noted.

No abstract

Failures of the aircraft control system sensors can cause both deterioration of stability and controllability characteristics and the inability of safe automatic control. It is necessary to detect and isolate such failures to determine the time and place of their occurrence in order to disable failed sensors or to diagnose them subsequently for reconfiguration during the flight. The direct use of traditional parametric approaches for sensors health monitoring by using their mathematical models is impossible due to the lack of data about the true information input signals received by their sensitive elements. This leads to the necessity of solving the problem of modeling the aircraft flight dynamics with a high level of uncertainties, which makes it difficult to utilize the functional control methods and necessitate the use of excessive sensor hardware redundancy. Well-known nonparametric methods either require a priori knowledge base, preliminary training or long-term tuning on a large volume of real flight data or have low selective sensitivity for reliable detection of failed sensors. In this work, the original nonparametric criterion for detecting and isolating sensors failures is derived. Its sensitivity is analyzed by using a complete nonlinear mathematical model of aircraft flight dynamics with a regular flight control system. The theoretical value and the criterion sensitivity coefficients are determined. The formula for the automatic evaluation of the float criterion threshold value is given. A high convergence of the results with theoretical ones is shown. This makes it possible to use the obtained criterion not only for the instant detection and isolation of sensors failures, but also for preliminary diagnostics of their quantitative characteristics.