Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

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Author: search.filters.author.Yılmaz, SinanSubject: search.filters.subject.Feedback control

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  • Conference Object
    Neuro-Fuzzy Controller in Real-Time Feedback Schedulers
    (Izmir Institute of Technology, 2002) Ayav, Tolga; Yılmaz, Sinan
    Traditional scheduling algorithms worked on closed and highly predictable environments. However present day systems need to work in more open and unpredictable environments; such as mobile robots, on-line trading, e-commerce, multimedia that cannot be driven well with traditional open-loop algorithms. A new scheduling paradigm, feedback control scheduling, therefore has been presented recently to fulfil the requirements of such systems. This algorithm defines error terms for schedules, monitors the error, and continuously adjusts the schedule to maintain stable performance. When PID (Proportional-Integral-Derivative) controller is used to control the CPU utilization, one of the problems faced is that when utilization setpoint is closer to 100%, in severely overloaded conditions, systems can have a longer settling time than the analysis based on the linear model since utilization feedback saturates at 100%. To overcome this problem, a neuro-fuzzy controller is designed instead of PID. Simulations showed that settling time with the neuro-fuzzy controller is approximately four times shorter than the one with the PID controller.
  • Conference Object
    Stability Properties of Adaptive Real-Time Feedback Scheduling: a Statistical Approach
    (Nessuna, 2004) Ayav, Tolga; Ferrari-Trecate, Giancarlo; Yılmaz, Sinan
    This paper focuses on the statistical analysis of an adaptive real-time feedback scheduling technique based on imprecise computation. We consider two-version tasks made of a mandatory and an optional part to be scheduled according to a feedback control rate-monotonic algorithm. A Proportional-Integral-Derivative (PID) control action provides the feedback strategy for deciding about the execution or rejection of the optional sub-tasks. By modelling the task execution times as random variables, we compute the probability density of the CPU utilization and derive conditions on PID parameters guaranteeing the stability of the overall system around a desired level of CPU utilization. This allows us to highlight the tasks statistics and the scheduling parameters that affect critically stability. The analysis is developed by first exploiting a number of simplifying assumptions that are progressively removed. The main results are also demonstrated through monte-carlo simulations of the scheduling algorithm.