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Showing 4 results for Subject: Control Applications

Ms Safiye Sheikhalishahi, Mr Sajjad Aghasizade Shaarbaf, Dr Mehdi Mirzaei, Dr Rahim Khoshbakhti Saray,
Volume 1, Issue 2 (1-2014)
Abstract

The control strategy in hybrid electric vehicles (HEV) determines the energy management between an internal combustion (IC) engine and an electric machine to generate the power required to drive the vehicle. In this study, the parameters of an electric assist control strategy of HEV, which is used in ADVISOR software, are optimized by minimizing the fuel consumption while maintaining the engine emissions below the Euro3 standard. In this way, a parallel HEV has been simulated in two drive cycles and the optimal parameters of controller are obtained by the genetic algorithm (GA). The simulation results show that by optimizing the control parameters, the fuel consumption decreases while satisfying the Euro3 standards and other constraints in various drive cycles. Also, different values for optimal parameters have been extracted. This indicates that the optimal parameters of the controller are dependent on the drive cycle.
Dr Sehraneh Ghaemi, Miss Farnaz Ghanbarpour,
Volume 1, Issue 2 (1-2014)
Abstract

In this paper, a new approach for controller designing of robust output feedback model reference adaptive control with a function of tracking error for a class of continuous linear systems with multiple uncertain time varying state delays is introduced. Proposed controller is not only robust versus of multiple uncertain time delays and external disturbance with uncertain bound but also improve performance of transient and steady state of closed loop system. The stability of closed loop system and error convergence is shown with an appropriate Lyapunov-Krasovskii function. Simulation results show good performance of proposed controller.
Askar Azizi, Sirus Bibak, Hamid Nourisola, Mohammadali Badamchizadeh,
Volume 2, Issue 1 (6-2014)
Abstract

Generally nonlinear modelling of aerospace system has uncertainty in model parameters and also in real situation different disturbances are applied to system. In spite of these uncertainties and disturbances, autopilot control system should be guarantee stability and desired performance of system. The conditions such as fast response, low tracking error, system robustness must be considered in autopilot design. In this paper, a new method is suggested to reduce the tracking error and increase system robustness. The proposed method is based on Backstepping approach. To reduce the tracking error, resulted from the simplification of the missile model, a nonlinear disturbance observer is used to estimate the uncertainty and also update the reference signal. In addition nonlinear disturbance observer is used to eliminate output disturbance. The advantage of the proposed method is its complete flexibility and also it can be employ for linear and nonlinear systems
Mr. Kazem Shokoohi-Mehr, Dr. Mohsen Farshad, Dr. Ramazan Havangi, Dr. Nasser Mehrshad,
Volume 7, Issue 2 (3-2021)
Abstract

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.


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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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