Journal of Majlesi Journal of Mechatronic Systems
Volume:5 Issue: 2, Jun 2016

In this article, the identification problem of a practical two degree-of-freedom (DOF) tracker system is investigated. The analytical modeling of two-DOF gimbal system as the main core of the tracker for both elevation and azimuth axes are introduced. By simplification and discussion on the governing equations, suitable structure of the model for identification is obtained. By performing identification procedure on the experimental system in the elevation and azimuth axes, the simplified models of this system are obtained through Recursive Least Square (RLS) approach. This is performed by using the practical data obtained from gyro in each axis of the under study system. As it can be interpreted and predicted from theoretical model, the identification process leads to a non-minimum phase model which depends on the operational points. This identified model can be used in stabilization and tracking loops in the control system design stage. The identification results in comparison with theoretical and experimental data are discussed. The adaptive or robust controllers are suitable candidates for controlling tracker system, where in the both controllers use this simplified model as the nominal or reference model.

In this paper, the complete structure of an educational robot with the ability to schedule a remote and graphical programming environment based on dedicated icons is proposed. The target of simplification of robotics, programming of education and connection of hardware and software is achieved. The idea is based on the educational robots used in schools and laboratories, which utilizing their own icon based graphical programming environment can be programmed. Wired and wireless networks can be used for remote control and no knowledge of programming. The application of the proposed idea in industrial and educational robotics and internet of things is presented.

Interval type-2 fuzzy logic system permits us to model rule uncertainties and every membership value of an element is interval itself. This study aims to propose a framework for an interval type-2 possibilistic fuzzy regression model. . In this model, vagueness is minimized, under the circumstances where the h-cut of observed value is included in predicted value. In this model both primary and secondary membership function of predicted value fit the observed value.

In this paper, designing a predictive model of a heat exchanger by using a multilayer perceptron (MLP) neural network and a local linear neuro-fuzzy network (LLNF) is presented. Local linear model tree algorithm (LOLIMOT) is used for training LLNF network, and gradient descent (GD) and Levenberg–Marquardt (LM) methods are used for training MLP network. There are two methods to apply data to MLP network. Both methods have been used in training MLP network and finally results of all methods have been compared together. The obtained results show that even though various training methods are applied to MLP network, this network is not able to give better results compared to the LOLIMOT algorithm. However, results of all models are acceptable and have minor differences with each other.

In this paper, the designing and simulation of an unmanned aerial vehicle (UAV) autopilot system using Fuzzy Logic Controller (FLC) is studied. At first the UAV mathematical model is explained by dynamic equations. Then, the FLC is designed considering the controller output variables, their range changes and the controller effects on the UAV are simulated. The controller is able to control the UAV automatically in specified track and height selected by the user by controlling the levels command and the aircraft speed. The controller is designed in such a way that would be used without changing the overall control algorithm. It can be used for most of UAVs just with small changes.

In this paper, a method nonlinear controller design is proposed for the synchronization of chaotic systems to the steady state the slave system as well as to be tracking of any desired trajectory to be achieved in a systematic way. The control analysis is based on the nonlinear control approach that interlaces the appropriate choice of a Lyapunov function. The numerical simulation results show that the proposed controller can force the Slave system dynamics, to move in the direction of the master system dynamics, on the other hand, the synchronization error will be asymptotically to zero.

The control of a space cam robot has been the primary objective of this study. A Samen robot is a type of a mobile space cam that is capable of moving from side to side similar to a spider. Samen Robot is a cable-driven parallel robot which is widely being used in stadium complexes for tracking some things such as footballers, In fact, at a certain height, the ball and the players are tracking on the football field. That is a path by considering the obstacles .This means finding the shortest or optimal path between the players (obstacles). The main topic in this article, finding the best and most optimal path must be tracked by Samen space cam. Kinematics and dynamic equations of this robot are presented. Then, in order to control of the robot, a PID controller method is proposed this controller requires the robot system states to be available. Therefore, the extended Kalman filter is employed to observe those states. Final after setting and controlling the path planning problem by considering the obstacle becomes a constrained optimization problem that must solve by PSO. Finally, with regard to these results, we can be assured in use constrained optimization method in Samen Planning.