Gene

Adaptive control

Control (management)

Temperature control

Engineering

Control system

Control engineering

Robustness (evolution)

Biochemistry

Computer science

PID controller

Artificial intelligence

Chemistry

Control theory (sociology)

Electrical engineering

In this paper, four different types of optimization technique for PID controller were designed to achieve a robust flight control system for Ultrastick-25e, and study which is best performance and robustness against any internal and external system effects such as sensor's noise and wind turbulence and lack of model certainty. Two types of proposed optimization techniques produce fixed parameters for PID control as genetic algorithm and fractional order PID, and two other types of proposed optimization techniques produce adaptive parameters as adaptive PID fuzzy tuned, PID tuned using local optimal control. Fixed parameters PID control is less than adaptive parameters PID control in terms of for performance robustness and stability, adaptive parameters change with system changes. Comparisons and simulations were made between the four types of control systems proposed under normal conditions and sensor's noise and wind turbulence and lack of model certainty, to evaluate which is the best type design. The results showed that adaptive parameters PID control, especially PID tuned using local optimal control, is the best type of proposed control system.

Robust PID Flight Controller for Ultrastick-25e UAV