2 research outputs found
Fuzzy-PID Controller for Azimuth Position Control of Deep Space Antenna
The Deep Space Antennas are essential in achieving communication over very large distances. However, the pointing accuracy of this antenna needs to be as precise as possible to enable effective communication with the satellite. Therefore, this work addressed the pointing accuracy for a Deep Space Antenna using Fuzzy-PID control technique by improving the performance objectives (settling time, percentage overshoot rise time and mainly steady-state error) of the system. In this work, the PID controller for the system was first of all designed and simulated after which, a fuzzy controller was also designed and simulated using MATLAB and Simulink respectively for the sake of comparison with the fuzzy-PID controller. Then, the fuzzy-PID controller for the system was also designed and simulated using MATLAB and Simulink and it gives a better performance objective (rise time of 1.0057s, settling time of 1.6019s, percentage overshoot of 1.8013, and steady-state error of 2.195e-6) over the PID and fuzzy controllers respectively. Therefore, the steady state error shows improved pointing accuracy of 2.195e-6
Fuzzy-PID Controller for Azimuth Position Control of Deep Space Antenna
The Deep Space Antennas are essential in achieving communication over very large distances. However, the pointing accuracy of this antenna needs to be as precise as possible to enable effective communication with the satellite. Therefore, this work addressed the pointing accuracy for a Deep Space Antenna using Fuzzy-PID control technique by improving the performance objectives (settling time, percentage overshoot rise time and mainly steady-state error) of the system. In this work, the PID controller for the system was first of all designed and simulated after which, a fuzzy controller was also designed and simulated using MATLAB and Simulink respectively for the sake of comparison with the fuzzy-PID controller. Then, the fuzzy-PID controller for the system was also designed and simulated using MATLAB and Simulink and it gives a better performance objective (rise time of 1.0057s, settling time of 1.6019s, percentage overshoot of 1.8013, and steady-state error of 2.195e-6) over the PID and fuzzy controllers respectively. Therefore, the steady state error shows improved pointing accuracy of 2.195e-6