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Showing 2 results for Havangi

Mr. Kazem Shokoohi-Mehr, Dr. Mohsen Farshad, Dr. Ramazan Havangi, Dr. Nasser Mehrshad,
Volume 7, Issue 2 (3-2021)

Due to the inefficiency of Kalman filter-based methods for combining low-cost inertial navigation system data and global satellite navigation systems when satellite signals are outage, the use of artificial intelligence techniques in integrated architecture has become a common issue. Therefore, in this paper, while presenting an effective hybrid architecture, the generalized regression neural network is used to predict the required observations of the Kalman filter at the event of long-term outage of satellite signals. In the proposed model, for training the neural network, the velocities and positions of the inertial system are considered as inputs and also the velocities and positions of the global positioning system are considered as network outputs. This approach, while being practical and operational, has reduced computational time and increased the accuracy and speed of training and network estimation. The simulation results show that due to the simple yet robust structure of the proposed architecture and of course the selection of an efficient multi-input-multi-output neural network with the ability to detect the effective relationship between inputs and specified outputs and consequently correct errors related to speeds and situations, inertial navigation system can be used for real-time navigation, self-reliant, with high reliability and accuracy.

Simin Hosseinzadeh, Dr Ramazan Havangi,
Volume 10, Issue 1 (3-2023)

Disturbance and uncertaities exist in industrial systems and greatly affect the performance and stability of these systems. The robotic manipulator is one the most widely used devices in the industry that is highly affected by various disturbances. Hence establishing a proper control algorithm to estimate and eliminate disturbances seems crucial. Since the robotic manipulator is a highly nonlinear system, we need to design a nonlinear disturbance observer. In this thesis a nonlinear disturbance observer is proposed to estimate the constant and oscillatory disturbances in the studied system. On the other hand, since proportional-derivative controllers (PD) are widely used in industrial systems, so in this thesis, a suitable proportional derivative controller will be designed. This controller is not capable of dealing with disturbances and uncertainties, so a new supervisory controller structure has been proposed to estimate disturbances and stabilize the system. The core of proposed controller uses a new sliding model controller. Finally, some comparisions with PD and super twisting sliding mode controllers have been performed in several cases and the numerical results show the advantages of the proposed controller.

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سامانه های غیرخطی در مهندسی برق Journal of Nonlinear Systems in Electrical Engineering
نشریه سامانه‌های غیرخطی در مهندسی برق در خصوص اصول اخلاقی انتشار مقاله، از توصیه‌های «کمیته بین‌المللی اخلاق نشر» موسوم به COPE و «منشور و موازین اخلاق پژوهش» مصوب معاونت پژوهش و فناوری وزارت علوم، تحقیقات و فناوری تبعیت می‌کند.
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