A Comparative Study on The Tuning of The PID Flight Controllers Using Swarm Intelligence

Abstract

QUAVs have some shortcomings in terms of nonlinearities, coupled dynamics, unstable open–loop characteristics, and they are prone to internal and external disturbances. Therefore, control problem of the QUAVs is still an open issue. Designed controllers based on the linear dynamics have limited operating ranges. Therefore, nonlinear dynamics of the QUAVs must be derived and used in the control problem. Although some advanced controllers are presented for QUAV control, PID controllers are the most employed, well–known controllers with the simple structure, ease of implementation, solid functionality and robustness amongst the variations up to a degree. In this paper, PID based controllers are proposed for the nonlinear attitude dynamics to overcome the control problem of the QUAVs. However, since optimality and tuning of the PID controllers are fuzzy because of trial and error approaches, swarm intelligence based meta-heuristic algorithms (ABC, ACO and PSO) are employed to optimize the PID coefficients. Results are compared in terms of transient analysis and MC analysis to cover the rise time, settling time, percentage overshoot, steady–state error for the former and stochastic fitness evaluation for the latter, respectively.

Tuning PID controller parameters of the DC motor with PSO algorithm

“…While the steady-state error that may occur in the system is eliminated in the integral effect, the response speed and stability of the system are increased in the derivative effect. Thus, the PID control method makes the steady-state error zero in the system and ensures a fast and stable system response [20,21]. Block diagram of the PID is given in Fig.…”

Modeling and Control of a Fixed-Wing High-Speed UAV

“…The open-loop system response of the mini-UAV against doublet elevator and rudder inputs with a 5-degree deflection angle is investigated in both longitudinal and lateral directions with the help of a code developed in MATLAB/Simulink. Finally, two different linear controllers, which are PID (Kaba, 2020) and LQR, are designed for mini-UAV, and timedependent results are compared with elevator effort.…”