Conference proceeding
Optimal PD Tracking Control of a Quadcopter Drone Using Adaptive PSO Algorithm
2018 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL, INFORMATICS AND ITS APPLICATIONS (IC3INA), pp.146-151
2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA) (Tangerang, Indonesia, 01/11/2018 - 02/11/2018)
01/01/2018
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Source: InCites
Abstract
Trajectory tracking control for quadcopter drone is a challenging work since the system is multi-input multi-output system, highly non-linear rigid body dynamics and severe cross-coupling. This paper copes that challenges by proposing the adaptive particle swarm optimization (APSO) to optimize the gains of proportional-derivative (PD) controller. The effectiveness of the proposed control algorithm is tested under constant and varying step functions as well as sine function. PSO-based optimal PD and Ziegler-Nichols (ZN)-based optimal PD controllers are taken as benchmarks. The results show that the APSO-PD controller produces shorter settling time with no overshoots than the benchmarks under the predefined trajectories.
Details
- Title
- Optimal PD Tracking Control of a Quadcopter Drone Using Adaptive PSO Algorithm
- Creators
- Edwar Yazid - Indonesian Institute of SciencesMatthew Garrat - University of New South WalesFendy Santoso - University of New South Wales
- Contributors
- A L Latifah (Editor)
- Publication Details
- 2018 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL, INFORMATICS AND ITS APPLICATIONS (IC3INA), pp.146-151
- Conference
- 2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA) (Tangerang, Indonesia, 01/11/2018 - 02/11/2018)
- Publisher
- IEEE
- Number of pages
- 6
- Grant note
- University of New South Wales-ADFA Australia
- Identifiers
- 991013092523402368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Conference proceeding