Helicopter Stabilization Using Integer and Fractional Order PID Controller Based on Genetic Algorithm

Abstract

Fractional Order Proportional, Integral, Derivative (FOPID) controller is a modified Proportional Integral Derivative (PID) controller, which has fractional orders for its derivative and integral parts rather than an integer. Two techniques, namely, PID and FOPID, are adopted to design and implement a Three Degree of Freedom (3DOF) control system to stabilize pitch, roll and travel axes of the helicopter system. In this study, an improvement in the performance of the controllers is achieved using the Genetic Algorithm (GA) optimization method which is employed to find optimum parameter values for controller gains. The helicopter control system is modeled mathematically and then simulated using MATLAB environment to verify the performance of the proposed PID and FOPID controllers based on the GA tuning method. Simulation results suggest that the GA-FOPID controller compared with GA-PID controller can achieve faster and more stable control performance for the 3DOF helicopter system.

Satellite Tracking Control System Using Different Optimal Controllers Based on Evolutionary Optimization Techniques

“…Over time, various controller models have been proposed to tackle the problem of antenna pointing in satellite as well as to track moveable target utilizing servomechanism system [3], [4], [5] and [6]. The aim of the proposed controller is to make the system meets the desired requirements regarding overshoot, rise time, settling time and steady-state error while maintaining the system's high stability and robustness, also, at the same time, providing the system with ability to reject any disturbance and noise [7]. Optimal controllers based on evolutionary techniques are proposed in order to design and preform a Two Degree of Freedom (2DOF) control system to stabilize the satellite tracking control system's azimuth and elevation angles.…”

Satellite Tracking Control System Using Optimal Variable Coefficients Controllers Based on Evolutionary Optimization Techniques

“…Various control models have been presented over time to address the problem of antenna positioning in satellite systems and to track moveable targets using servomechanism [2,3]. The suggested controller's goal is to ensure that the system meets the appropriate requirements regarding overshoot, rise time, settling time and steady-state error while retaining the system's high stability, also, at the same time, providing the system with capacity to reject any disturbance and noise [4]. Optimal controllers based on evolutionary optimization approaches are suggested in order to design and 327 perform a two degree of freedom (2DOF) control system to stabilize the azimuth and the elevation angles of the satellite tracking control system.…”