Showing 5 results for Optimal Control
Z. Nasiri-Gheidari, H. Lesani, F. Tootoonchian,
Volume 2, Issue 3 (7-2006)
Abstract
Hunting is a flutter associated with the synchronous speed that gives rise to the
gyro drifting errors and may cause objectionable time-displacement errors in video head
wheel drives and other precision scanning systems. In this paper, dynamic characteristics of
permanent Magnet hysteresis motors are presented and hunting is explained. New damping
techniques have been developed using optimized eigenvalues calculation. They are
calculated from LQR optimization method. In this damping method, a distinct reduction in
hunting has been archived. Furthermore field oriented control result of motor is presented
that have good effect on Hunting. Nearest agreement between simulated and measurement
results shows the accuracy of motor model. Comparison between this paper results and
other measured damping methods result are shown its success.
M. E. Haji Abadi, H. Rajabi Mashhadi,
Volume 9, Issue 3 (9-2013)
Abstract
In this paper, the continuous optimal control theory is used to model and solve the maximum entropy problem for a continuous random variable. The maximum entropy principle provides a method to obtain least-biased probability density function (Pdf) estimation. In this paper, to find a closed form solution for the maximum entropy problem with any number of moment constraints, the entropy is considered as a functional measure and the moment constraints are considered as the state equations. Therefore, the Pdf estimation problem can be reformulated as the optimal control problem. Finally, the proposed method is applied to estimate the Pdf of the hourly electricity prices of New England and Ontario electricity markets. Obtained results show the efficiency of the proposed method.
A. Younesi, S. Tohidi, M. R. Feyzi,
Volume 14, Issue 3 (9-2018)
Abstract
Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be implemented in real time. In order to solve this problem, this paper presents an improved strategy in the field of nonlinear MPC (NMPC) of the permanent magnet synchronous motor (PMSM). The proposed method applies a sequence of reduction weighting coefficients in the cost function, over the prediction horizon. By using the proposed strategy, NMPC give a more accurate response with less number of prediction horizon. This means the computational time is reduced. It also suggests using an incremental algorithm to reduce the computational time. Performance of the proposed Nonlinear MPC (NMPC) scheme is compared with the previous NMPC methods via simulations performed by MATLAB/Simulink software, in permanent magnet synchronous motor drive system. The results show that the use of proposed structure not only lowers prediction horizon and hence computational time, but also it improves speed tracking performance and reduces electromagnetic torque ripple. In addition, using the incremental algorithm also reduces the computational time which makes it suitable for real-time applications.
R. Babaie, A. F. Ehyaei,
Volume 15, Issue 2 (6-2019)
Abstract
In this paper, using the State Dependent Riccati Equation (SDRE) method, we propose a Robust Optimal Integral Sliding Mode Controller (ROISMC) to guarantee an optimal control law for a quadrotor which has become increasingly important by virtue of its high degrees of manoeuvres ability in presence of unknown time-varying external disturbances and actuator fault. The robustness of the controller is ensured by an Integral Sliding Mode Controller (ISMC). Subsequently, based on Luenberger linear state estimator, the control algorithm is reformed and the actuator’s faults are detected. Moreover, design of the controller is based on Lyapunov method which can provide the stability of all system states during the tracking of the desired trajectory. The stability of suggested algorithm is verified via the execution of sudden maneuvers subjected to forcible wind disturbance and actuator faults while performing accurate attitude and position tracking by running an extensive numerical simulation. It is comprehended that the proposed optimal robust method can achieve much better tracking capability compared with conventional sliding mode controller.
Zahra Mobini-Serajy, Mehdi Radmehr, Alireza Ghorbani,
Volume 21, Issue 1 (3-2025)
Abstract
Microgrids harness the benefits of non-inverter and inverter-based Distributed Energy Resources (DER) in grid-connected and island environments. Adoption of them with the various types of electric loads in modern MGs has led to stability and power quality issues. In this paper, a two-level control approach is proposed to overcome these problems. A state-space dynamic model is performed for Micro-Grids, for this goal, the state-space equations for generation, network, and load components are separately developed in a local DQ reference frame, and after linearization around the set point, then combining them into a common DQ reference frame. In the first level, the control of inverter-based DERs and some types of loads with fast response are activated, and in the second level, the control of synchronous diesel generator resources with slower response is used. In order to validate and evaluate the effectiveness of the proposed control approach, numerical studies have been established on a standard test MG under normal and symmetrical three-phase fault conditions. Finally, the simulation results are summarized.
