Aerospace Science and Technology
Amir reza Kosari; Elahe Khatoonabadi; Vahid Bohlouri
Abstract
In this paper, the control of a three-axis rigid satellite attitude control system with a fractional order proportional-integral-derivative (PID) controller is investigated in the presence of disturbance and parametric uncertainties. The reaction wheel actuator with the first-order dynamic model is used ...
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In this paper, the control of a three-axis rigid satellite attitude control system with a fractional order proportional-integral-derivative (PID) controller is investigated in the presence of disturbance and parametric uncertainties. The reaction wheel actuator with the first-order dynamic model is used to control the attitude of the satellite. Uncertainties are considered on satellite moment inertia, actuator model and amplitude and frequency of external disturbances. External disturbances are modeled with two fixed and periodic parts and uncertainty is also considered on the disturbances model. The integer order controller is also used for the same conditions to compare the results with the fractional order controller. The usual Granwald-Letinkov definition is used to solve integrals and fractional order derivatives. The mean absolute of the pointing error of the satellite pointing maneuver has been selected as an objective function of the optimization problem. The controller gains in integer and fractional order are obtained by particle swarm evolution algorithm (PSO) optimization method. The performance criterion has been studied in terms of the controller time response and also in terms of the standard deviation of the mentioned uncertainties and external disturbance. The results show that the fractional order controller performs more accurate and robustness than the integer order controllers in the face of uncertainty and disturbance.
Abolfazl Mokhtari; A.A. Nikkhah; Mahdi Sabze Parvar; A.R. Novinzadeh
Volume 9, Issue 2 , September 2012
Abstract
There is a growing interest in the modeling and control of model helicopters using nonlinear dynamic models and nonlinear control. Application of a new intelligent control approach called Brain Emotional Learning Based Intelligent Controller (BELBIC) to design autopilot for an autonomous helicopter is ...
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There is a growing interest in the modeling and control of model helicopters using nonlinear dynamic models and nonlinear control. Application of a new intelligent control approach called Brain Emotional Learning Based Intelligent Controller (BELBIC) to design autopilot for an autonomous helicopter is addressed in this paper. This controller is applied to a nonlinear model of a helicopter. This methodology has been previously proved to present robust characteristics against disturbances and uncertainties existing in the system. The simulation results of this controller has compared with a PID controller. The policies for PID and BELBIC controller are the same. The controller design goal is that the helicopter tracks a special maneuver to reach the commanded height and heading. The performance of the controllers is also evaluated for robustness against perturbations with inserting a high frequency disturbance. Simulation results show a desirable performance in both tracking and improved control signal by using BELBIC controller.