تشخیص و جداسازی عیب مبتنی بر فیلتر کالمن مقاوم در سیستم‌‌‌های زمان گسسته با نامعینی تصادفی و کران‌دار

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی برق-کنترل، دانشکده فنی و مهندسی، دانشگاه بین المللی امام خمینی، قزوین، ایران

2 گروه مهندسی برق-کنترل، دانشکده فنی و مهندسی، دانشگاه بین المللی امام خمینی

چکیده

این مقاله به مسأله تشخیص و جداسازی عیب در سیستم‌های گسسته متغیر با زمان، با داشتن نامعینی تصادفی، کران‌دار و وجود نویز در سیستم و حس‌گر می‌پردازد. عیوب می‌تواند به‌طور همزمان یا به ‌طور متوالی رخ دهند، از این‌رو فیلتر طراحی‌شده توانایی تشخیص و جداسازی این عیوب را، با توجه به چالش‌های ایجادشده به علت وجود نامعینی و اثرات نویز داراست. در حل مساله تشخیص عیب، به طراحی و ارائه فیلتر تشخیص و جداساز عیب مقاوم مبتنی بر فیلتر کالمن مقاوم پرداخته خواهد شد. به همین منظور، آستانه‌ای به‌صورت متغیر با زمان براساس حد بالای کوواریانس مانده‌ها تعریف می‌شود. این حد آستانه به تشخیص بهتر کمک می‌کند و از اخطار اشتباه در تشخیص عیوب جلوگیری می‌کند. در طراحی تشخیص‌گر عیب به تعداد خروجی‌های سیستم تشخیص‌گر طراحی می‌شود ، هم‌چنین برای طراحی جداساز عیب با بررسی مانده‌های سیستم شروطی به دست می‌آید که با اعمال این شروط در طراحی، به یک جداساز عیب مقاوم دست می‌یابد. در انتها با استفاده از سه مثال کارایی و عملکرد روش پیشنهادی نشان داده خواهد شد. در مثال اول عملکرد روش پیشنهادی در حضور عدم قطعیت و نویز نشان داده می‌شود و در مثال‌های دوم و سوم عملکرد و کارایی روش خود را با روش‌های دیگر مقایسه و برتری این روش در حضور نامعینی نشان داده خواهد شد.
 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Fault detection and isolation based on robust Kalman filter for discrete-time systems with stochastic and norm-bounded uncertainties

نویسندگان [English]

  • Amir Hossein Barati 1
  • Mehdi Rahmani 2
1 Department of Electrical Engineering-Control, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran
2 Department of Electrical Engineering (control), Faculty of Engineering and Technology, Imam Khomeini International University
چکیده [English]

This paper deals with the problem of fault detection and isolation for discrete time-varying systems with stochastic and bounded uncertainties, and in presence of noises in the plant and sensors. Faults can occur simultaneously or sequentially, so the designed filter has the ability to detect and isolate these faults, and handle the challenges posed by uncertainty and the effects of noises. In solving the problem of fault diagnosis, fault detection and isolation filter based on the robust Kalman filter are presented. For this purpose, a time-varying threshold is defined based on the upper bound of covariance of the residuals. This threshold helps in better performance and prevents misdiagnosis. In the design of the fault detector, due to the number of outputs, fault detectors are designed. Moreover, by examining the residuals of the system, some conditions are obtained, which, by applying these conditions, a robust fault isolator is achieved. Finally, using three examples, the efficiency and performance of the proposed method are shown. In the first example, the performance of the proposed method is studied in the presence of uncertainty and noise, and in the second and third examples, the performance of the method is compared with other methods and the superiority of the proposed approach in the presence of uncertainties is shown.

کلیدواژه‌ها [English]

  • Fault detection
  • Fault isolation
  • Robust Kalman filter
  • Discrete-time system
  • Uncertainty
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