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kalman filter algorithm

در نشریات گروه برق
تکرار جستجوی کلیدواژه kalman filter algorithm در نشریات گروه فنی و مهندسی
تکرار جستجوی کلیدواژه kalman filter algorithm در مقالات مجلات علمی
  • Akram Asghari Govar *
    One of the most important symptoms of epilepsy is convulsions, whose detailed analysis is performed by electroencephalography (EEG) signal. Electroencephalogram, as a clinical tool to illustrate the electrical activities of the brain accurately, provides an appropriate method for diagnosing epilepsy disorders, which plays an important role in identifying this disease, especially seizures. Seizures resulting from epilepsy may have negative physical, psychological, and social consequences such as loss of consciousness and sudden death. With timely and correct identification of epilepsy, its effect can be treated with medicine or surgery. In this thesis, a brief review of the methods of identifying epilepsy using EEG signal analysis along with the separation of epileptic signals from healthy and normal signals has been done. Methods based on EEG analysis, from non-linear methods of signal processing, provide much better results due to the properties of signal dynamics
    Keywords: Epileptic seizures, electroencephalogram (EEG) signal, Wavelet Transform, Kalman filter algorithm, neural noises
  • Saeed Tavakoli , Hamid Fasih, Jafar Sadeghi, Hamed Torabi
    In this paper, a novel centralized controller is presented to control multi-input multi-output industrial processes with heavy interactions and significant time-delays. The system model equations are represented in a non-minimal stochastic state-space form. Also, the state and measurement equations respectively use smoothed random walk model and finite impulse response model of the plant. To design the controller, a quadratic cost function is considered. A standard Kalman filter algorithm is used to estimate the state vector of the controller and solve to the discrete algebraic Riccati equation simultaneously. By using the smoothing parameter, the controller behavior can be changed between the Kalman filter random walk controller and the Kalman filter integrated random walk controller. To evaluate the effect of the smoothing parameter the proposed controller is first applied to a single input single output system. Then an industrial-scale polymerization reactor which has the two-input and two-output system is used to investigate the performance of the designed controller. The simulation results indicate that the controller has a good performance in tracking the set point and robust due to changing the system parameters.
    Keywords: Centralized controller, Industrial-scale polymerization reactor, Kalman filter algorithm, Multi-input multi-output process
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