In this paper the dynamic behavior of linear induction motor is described by a mathematical model taking into account the end effects and the core losses. The need for such a model rises due to the complexity of linear induction motors electromagnetic field theory. The end affects are modeled by introducing a speed dependent scale factor to the magnetizing inductance and series resistance in the d-axis equivalent circuit. Simulation results are presented to show the validity of the model during both no-load and sudden load change intervals. This model can also be used directly in simulation researches for linear induction motor vector control drive systems.
The Leader detecting and following are one of the main challenges in designing a leader-follower multi-robot system, in addition to the challenge of achieving the formation between the robots, while tracking the leader. The biological system is one of the main sources of inspiration for understanding and designing such multi-robot systems, especially, the aggregations that follow an external stimulus such as light. In this paper, a multi-robot system in which the robots are following a spotlight is designed based on the behavior of the Artemia aggregations. Three models are designed: kinematic and two dynamic models. The kinematic model reveals the light attraction behavior of the Artemia aggregations. The dynamic model will be derived based on the newton equation of forces and its parameters are evaluated by two methods: first, a direct method based on the physical structure of the robot and, second, the Least Square Parameter Estimation method. Several experiments are implemented in order to check the success of the three proposed systems and compare their performance. The experiments are divided into three scenarios of simulation according to three paths: the straight line, circle, zigzag path. The V-Rep software has been used for the simulation and the results appeared the success of the proposed system and the high performance of tracking the spotlight and achieving the flock formation, especially the dynamic models.
The identification of system parameters plays an essential role in system modeling and control. This paper presents a parameter estimation for a permanent magnetic DC motor using the simulink design optimization method. The parameter estimation may be represented as an optimization problem. Firstly, the initial values of the DC motor parameters are extracted using the dynamic model through measuring the values of voltage, current, and speed of the motor. Then, these values are used as an initial value for simulink design optimization. The experimentally input- output data can be collected using a suggested microcontroller based circuit that will be used later for estimating the DC motor parameters by building a simulink model. Two optimization algorithms are used, the pattern search and the nonlinear least square. The results show that the nonlinear least square algorithm gives a more accurate result that almost approaches to the actual measured speed response of the motor. )
In this article, a robust control technique for 2-DOF helicopter system is presented. The 2-DOF helicopter system is 2 inputs and 2 outputs system that is suffering from the high nonlinearity and strong coupling. This paper focuses on design a simple, robust, and optimal controller for the helicopter system. Moreover, The proposed control method takes into account effects of the measurement noise in the closed loop system that effect on the performance of controller as well as the external disturbance. The proposed controller combines low pass filter with robust PID controller to ensure good tracking performance with high robustness. A low pass filter and PID controller are designed based H∞weighted mixed sensitivity. Nonlinear dynamic model of 2-DOF helicopter system linearized and then decoupled into pitch and yaw models. Finally, proposed controller applied for each model. Matlab program is used to check effectiveness the proposed control method. Simulation results show that the proposed controllers has best tracking performance with no overshot and the smallest settling time with respect to standard H∞and optimized PID controller.