Particle Swarm Optimization Tuned Fractional Order Sliding Mode Controller for Altitude Stabilization and Trajectory Tracking of Agricultural Monitoring Quadcopter
| dc.contributor.advisor | Lebsework, Negash (PhD) | |
| dc.contributor.advisor | Dereje, Shiferaw (PhD) | |
| dc.contributor.author | Belsty, Derseh | |
| dc.date.accessioned | 2021-11-15T06:53:23Z | |
| dc.date.accessioned | 2023-11-28T14:20:36Z | |
| dc.date.available | 2021-11-15T06:53:23Z | |
| dc.date.available | 2023-11-28T14:20:36Z | |
| dc.date.issued | 2021-10 | |
| dc.description.abstract | Quadcopter technology could help farmers around the world to monitor their agriculture to know accurate and up-to-date information quickly on the health of their crops and the environmental condition of the land. This thesis addresses particle swarm optimization tuned fractional-order sliding mode controller for altitude stabilization and trajectory tracking of agricultural monitoring UAV. First, the quadrotor dynamics are modeled using the Newton- Euler systems approach. Second, Fractional-order (FO) sliding mode control (SMC) system is developed for attitude and position trajectory tracking of a quadrotor unmanned aerial vehicle (UAV) system under unknown external disturbance. Quadcopter control algorism is divided into inner and outer control loops because the quadcopter is under actuated system, Where direct control of all six degrees of freedom is not possible. The outer loop controls the altitude and generates roll and pitch angle reference trajectories controlled in the inner loop. The inner loop controls attitude (roll, pitch, and yaw) of the quadcopter. In order to achieve good task performance for agility, flying efficiency and trajectory tracking, particle swarm optimization (PSO) algorithms are used to obtain parameters of fractional order sliding mode controller (FOSMC). The comparison of conventional sliding mode control with fractional-order sliding mode controller is analyzed. The effectiveness of the proposed control scheme is verified by developing simulation results for the quadcopter study in MATLAB/SIMULINK software. In this work, different types of tasks are performed under different conditions. Indeed, the ability of the proposed controller to track the imposed trajectories and achieving of position in space is well seen from 3D path tracking simulations and even in presence of disturbances | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/28649 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | quadcopter | en_US |
| dc.subject | particle swarm optimization | en_US |
| dc.subject | fractional order sliding mode controller | en_US |
| dc.subject | Trajectory | en_US |
| dc.subject | Disturbance | en_US |
| dc.title | Particle Swarm Optimization Tuned Fractional Order Sliding Mode Controller for Altitude Stabilization and Trajectory Tracking of Agricultural Monitoring Quadcopter | en_US |
| dc.type | Thesis | en_US |