Mehdi Shahbazian

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This paper presents the state estimation problem for nonlinear industrial systems using asynchronous measurements to simulate the circumstances of real case studies. The well-known conventional Kalman filters give the optimal solution but require synchronous measurements, an accurate system model and exact stochastical noise characteristics. Thus, the(More)
Flow rates of oil, gas and water are most important parameters of oil production that is detected by Multiphase Flow Meters (MFM). Conventional MFM collects data on long-term, because of the radioactive source is used for detection and in unmanned location used due to being away from wells. In this work, a new method based on feed-forward artificial neural(More)
This paper presents a modified fuzzy control for speed control of induction motor (IM). At first, the PI controller is investigated for speed control of Induction Motor, and then fuzzy logic controller performance is simulated. Induction Motor performance is checked through the simulation studies in MATLAB/SIMULINK environment. Hybridization of fuzzy logic(More)
A multiple fault tolerant measurement system based on nonlinear dynamic models, special searching algorithm, principle components decomposition and Q test is developed. The proposed system uses a model-based estimator to deliver symptoms. The symptoms are then analyzed in a statistical unit in order to detect the faults and isolate the faulty sensors.(More)
— Wavelet neural network based on sampling theory has been found to have a good performance in function approximation. In this paper, this type of wavelet neural network is applied to modeling and control of a nonlinear dynamic system and some methods are employed to optimize the structure of wavelet neural network to prevent a large number of nodes. The(More)
Conventional PID controllers are still used in industry due to their simplicity in structure, and ability to eliminate steady state error in operating point. However, it is difficult to achieve a desired tracking control performance since for highly non-linear processes. In order to improve the set point tracking performance under aforementioned issues, a(More)
In this work, a fuzzy logic controller has been applied to control the top and bottom compositions in a binary distillation column. To improve the performance of fuzzy logic controller, Cuckoo optimization algorithm is proposed to optimize its parameters. Compared to ordinary fuzzy logic controller and PID controller, the proposed optimized fuzzy logic(More)
Sliding Mode Control (SMC) is a powerful methodology in the field of nonlinear feedback control with feature of proven robustness, performance and stability in the face of system nonlinearity and modeling uncertainties. Unfortunately, pure SMC controller suffers from two important problems; chattering phenomenon and formulation of equivalent dynamics. The(More)
Radial Basis Function Neural Network (RBFNN) is considered as a good applicant for the prediction problems due to it's fast convergence speed and rapid capacity of learning, therefore, has been applied successfully to nonlinear system identification. The traditional RBF networks have two primary problems. The first one is that the network performance is(More)