Abstract
This work aims to design an optimal fuzzy PD (FPD) control for the attitude and altitude stabilization of a quadrotor. The control design is done by mean of the particle swarm optimization (PSO) under the constraints of the controller interpretability and the saturation of the actuators. Concretely, a decentralized control structure is adopted where four FPD controllers are used to stabilize the quadrotor angles (roll, pitch and yaw) and height. A PSO-based algorithm is used to simultaneously tune the four constrained controllers regarding a cost function quantifying the whole system performances. The simulation results are presented to show the efficiency of the proposed approach.
Highlights
In the recent last years, the quadrotor unmanned aerial vehicles (UAVs) are become very familiar
A nonlinear fuzzy PD (FPD) controller can be reached by moving the input membership functions and/or the output singletons from their modal positions
Particle swarm optimization (PSO), initially introduce by Kennedy and Eberhart [14], is a heuristic optimization method inspired by the movement of individuals within a swarm
Summary
In the recent last years, the quadrotor unmanned aerial vehicles (UAVs) are become very familiar. The population-based optimization methods have been gained a special interest to solve the fuzzy controllers design problem; Genetic Algorithm (GA) [8], Particle swarm optimization(PSO) [9], Ant Colony Optimization (ACO) [10], Bees Algorithm [11], and Gravitational Search Algorithm (GSA) [12]. Among these methods, PSO is distinguished by the simplicity and the efficiency of the algorithm trough a continuous search space.
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