Hossein Sadegh Lafmejani

The renewable energy resources such as wind power have recently attracted more researchers’ attention. It is mainly due to the aggressive energy consumption, high pollution and cost of fossil fuels. In this era, the future fluctuations of these time series should be predicted to increase the reliability of the power network. In this paper, the dynamic characteristics and short-term predictability of hourly wind speed and power time series are investigated via nonlinear time series analysis methods such as power spectral density analysis, time series histogram, phase space reconstruction, the slope of integral sums, the  method, the recurrence plot and the recurrence quantification analysis. Moreover, the interactive behavior of the wind speed and wind power time series is studied via the cross correlation, the cross and joint recurrence plots as well as the cross and joint recurrence quantification analyses. The results imply stochastic nature of these time series. Besides, a measure of the short-term mimic predictability of the wind speed and the underlying wind power has been derived for the experimental data of Spain’s wind farm.

Fuzzy logic controller (FLC) is a heuristic method by If-Then Rules which resembles human intelligence and it is a good method for designing Non-linear control systems. In this paper, an arbitrary helicopter model includes articulated manipulators has been simulated with Matlab SimMechanics toolbox. Due to the difficulties of modeling this complex system, a fuzzy controller with simple fuzzy rules has been designed for its yaw and roll angles in order to stabilize the helicopter while it is in the presence of disturbances or its manipulators are moving for a task. Results reveal that a simple FLC can appropriately control this system.

In this paper, the modeling, simulation and control of 3 degrees of freedom articulated robotic manipulator have been studied. First, we extracted kinematics and dynamics equations of the mentioned manipulator by using the Lagrange method. In order to validate the analytical model of the manipulator we compared the model simulated in the simulation environment of Matlab with the model was simulated with the SimMechanics toolbox. A sample path has been designed for analyzing the tracking subject. The system has been linearized with feedback linearization and then a PID controller was applied to track a reference trajectory. Finally, the control results have been compared with a nonlinear PID controller.