An aerial robot for rice farm quality inspection with type-2 fuzzy neural networks tuned by particle swarm optimization-sliding mode control hybrid algorithm
Agricultural robots, or agrobots, have been increasingly adopted in every aspect of farming from surveillance to fruit harvesting in order to improve the overall productivity over the last few decades. Motivated by the compelling growth of the agricultural robots in modern farms, in this work, an au...
Main Authors: | Camci, Efe, Kripalani, Devesh Raju, Ma, Linlu, Kayacan, Erdal, Khanesar, Mojtaba Ahmadieh |
---|---|
Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139589 |
Similar Items
-
Learning Control of Fixed-Wing Unmanned Aerial Vehicles Using Fuzzy Neural Networks
by: Kayacan, Erdal, et al.
Published: (2017) -
Novel Levenberg–Marquardt based learning algorithm for unmanned aerial vehicles
by: Sarabakha, Andriy, et al.
Published: (2018) -
Optimal design of adaptive type-2 neuro-fuzzy systems: A review
by: Hassan, Saima, et al.
Published: (2017) -
Type-2 fuzzy elliptic membership functions for modeling uncertainty
by: Kayacan, Erdal, et al.
Published: (2020) -
Intuit before tuning : type-1 and type-2 fuzzy logic controllers
by: Sarabakha, Andriy, et al.
Published: (2020)