Ant Colony Optimization for Estimating Parameters of Flood Frequency Distributions

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.

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Ant Colony Optimization for Estimating Parameters of Flood Frequency Distributions

Cited by 2 publications

References 53 publications

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