Modeling of Unmanned Aerial Vehicles for Smart Agriculture Systems Using Hybrid Fuzzy PID Controllers
Abstract
:1. Introduction
2. Literature Review
3. Mathematical Modelling Approach and Quadcopter Controller Design for Smart Agriculture Applications
3.1. The Working Principles of Aerial Vehicle Guided Agriculture System
3.2. Mathematical Modeling of Quadcopter Motion
- ➢
- The structure is rigid
- ➢
- The structure is axis-symmetrical
- ➢
- The center of gravity and the body-fixed frame origin coincide
- ➢
- The propellers are rigid
- ➢
- Trust and drag are proportional to the square of the propeller’s speed.
3.3. Control Design for Quadcopter System Stabilization using Fuzzy PID
3.4. Quadcopter Path Planning Assistance System
3.5. Characteristics Analyzed for the UAV Response
3.6. Theoretical Analysis of the Proposed Results: Lyapunov Stability Criteria for Agricultural Drones
4. Results and Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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negative input (N) | negative input (N) | most negative (NNNN) |
negative input (N) | close to zero (C) | more negative (NNN) |
negative input (N) | positive input (P) | more negative (NN) |
close to zero (C) | negative input (N) | negative input (N) |
close to zero (C) | close to zero (C) | close to zero (C) |
close to zero (C) | positive input (P) | more positive (PP) |
positive input (P) | negative input (N) | more positive (PPP) |
positive input (P) | close to zero (C) | most positive (PPPP) |
positive input (P) | positive input (P) | most positive (PPPP) |
Cartesian Scheme | Quadcopter System Scheme |
---|---|
Specification | Automatic Tuned Controller Response (Fuzzy PID) | Classic Controller Response (PID) | Automatic Tuned Controller over Compensator (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
Low Fidelity | Medium Fidelity | High Fidelity | Low Fidelity | Medium Fidelity | High Fidelity | Low Fidelity | Medium Fidelity | High Fidelity | |
Roll | 1.55 s | 1.55 s | 1.55 s | 2.65 s | 2.65 s | 2.65 s | 41.5% | 41.5% | 41.5% |
Height | 3.55 s | 3.55 s | 2.8 s | 4.0 s | 5.0 s | 4.6 s | 11 | 11 | 17.4 |
Airspeed | 0.55 s | 0.55 s | 0.55 s | 0.68 s | 0.98 s | 0.98 s | 44 | 44 | 44 |
Specification | Current Work: Automatic Tuned Controller Response (Fuzzy PID) | Previous Works [24,25] | Current Work over Previous Work (%) (Fuzzy PID) | ||||||
---|---|---|---|---|---|---|---|---|---|
Low Fidelity | Medium Fidelity | High Fidelity | Low Fidelity | Medium Fidelity | High Fidelity | Low Fidelity | Medium Fidelity | High Fidelity | |
Roll | 1.55 s | 1.55 s | 1.55 s | 2.86 | 2.56 | 3.34 | 35.31% | 39.45% | 53.6% |
Height | 4.55 s | 4.55 s | 3.8 s | 4.89 | 4.86 | 4.94 | 7% | 7% | 8% |
Airspeed | 0.55 s | 0.55 s | 0.55 s | 1.97 | 0.92 | 0.98 | 72.08% | 41.22% | 43.88% |
Specifications | % (Fuzzy PID over PID) | % (Fuzzy PID over fuzzy) | |||
---|---|---|---|---|---|
Overshoot (%) | 0.5 | 0.25 | 0.05 | 90 | 80 |
Settling time (s) | 1.2 | 0.85 | 0.78 | 35 | 8.23 |
Rise time (s) | 1.5 | 0.98 | 0.65 | 56.67 | 33.67 |
Steady state error (%) | 0.09 | 0.05 | 0.025 | 72.22 | 50 |
Parameters Specification | Rise Time (s) | Settling Time (s) | Steady State Error | Overshoot | Stability |
---|---|---|---|---|---|
[20 30 80 120] | [1.8 1.6 0.9 0.5] | Small change | decreases ( | [0.01 0.1 0.4 0.6] | decreases ( |
[20 30 80 120] | [1.4 1.1 0.8 0.45] | increases | 0 | [0.1 0.3 0.5 0.7] | decreases ( |
[20 30 80 120] | Small change | decreases ( | No effect in theory | improvement if is small |
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Amertet, S.; Gebresenbet, G.; Alwan, H.M. Modeling of Unmanned Aerial Vehicles for Smart Agriculture Systems Using Hybrid Fuzzy PID Controllers. Appl. Sci. 2024, 14, 3458. https://doi.org/10.3390/app14083458
Amertet S, Gebresenbet G, Alwan HM. Modeling of Unmanned Aerial Vehicles for Smart Agriculture Systems Using Hybrid Fuzzy PID Controllers. Applied Sciences. 2024; 14(8):3458. https://doi.org/10.3390/app14083458
Chicago/Turabian StyleAmertet, Sairoel, Girma Gebresenbet, and Hassan Mohammed Alwan. 2024. "Modeling of Unmanned Aerial Vehicles for Smart Agriculture Systems Using Hybrid Fuzzy PID Controllers" Applied Sciences 14, no. 8: 3458. https://doi.org/10.3390/app14083458