Equivalent order reduction-based diagnosability evaluation method

Abstract

The invention discloses an equivalent order reduction-based diagnosability evaluation method. According to the method, firstly, the influences of process and observation noises and the uncertainty areconsidered and a diagnosability window model of a complex dynamic system is obtained. Secondly, based on the recurrence relation in the system, a diagnosability dimension reduction window model of the system is obtained. The burden of data storage and calculation is greatly reduced, and the diagnosability calculation efficiency of the system is improved. Finally, the diagnosability quantitative evaluation indexes of the complex dynamic system are obtained. According to the invention, the influences of process and observation noises and the uncertainty on the correctness of diagnosability evaluation results are comprehensively considered. Meanwhile, the influence of a time window model on diagnosability evaluation results is also considered. As a result, the diagnosability design level ofthe system can be maximally improved during the design stage of the system. A guidance basis is provided for the configuration of the system. The design method of the system is optimized and the design cost of the system is reduced.

Description

technical field [0001] The invention belongs to the technical field of aerospace control, and in particular relates to a diagnosability evaluation method based on equivalent reduction. Background technique [0002] Carrying out diagnosability evaluation research is to move the focus of improving system fault diagnosis capabilities to the design stage, and to find out the weak links of fault diagnosis in the entire system to the greatest extent, so as to improve the on-orbit performance of spacecraft control systems from the system level. It will further improve the autonomous fault diagnosis capability of the spacecraft, extend the service life of the spacecraft in orbit, and provide a theoretical basis and technical reserves for the design and development of subsequent background models such as deep space autonomous navigation and astronomical observation. [0003] Fault diagnosability is an important attribute of the control system itself, and it is an important index to m...

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Problems solved by technology

In fact, simply treating uncertainty as a random distribution will cause the evaluation results to lose accuracy, and this method cannot quantify the impact of uncertainty; the time window sequence has a greater impact on the calculation of diagnosability evaluation, which means that The calculation efficiency of the existing traditional methods is low, and at the same time, due to the constraints of limited computing and storage resources on the satellite, it also makes it difficult for the existing methods to be applied in orbit

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