Modeling and Rotation Control Strategy for Space Planar Flexible Robotic Arm Based on Fuzzy Adjustment and Disturbance Observer
Abstract
:1. Introduction
2. Modelling Dynamics for the SFRA
2.1. Friction Modeling
2.2. Dynamic Modeling
2.3. Dynamical Model Simplification
2.3.1. 1D1M Simplification Model
2.3.2. NNTs Simplification Model
3. Accuracy Evaluation of the Simplified Model
4. Fuzzy PI Control Based on Disturbance Observer
4.1. Fuzzy Adjustment of the Controller Parameters Based on Pole Configuration
4.2. Design of Disturbance Observer Based on the Nominal Model
5. Simulation and Physical Prototype Control Experiments on Ground
5.1. Simulation Analysis
5.2. Ground Physical Prototype Control Experiment
6. Discussions
6.1. Comparison of Dynamic Modeling Methods
6.2. DOB Robust Stability
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Condition | l (m) | M (kg) | (rad/s) | EI (Nm2) |
---|---|---|---|---|
Length 1 (a-i) | 1 | 3 | 1 | 160 |
Length 2 (a-ii) | 2 | 3 | 1 | 160 |
Length 3 (a-iii) | 3 | 3 | 1 | 160 |
Mass 1 (b-i) | 3.5 | 2 | 1 | 160 |
Mass 2 (b-ii) | 3.5 | 4 | 1 | 160 |
Mass 3 (b-iii) | 3.5 | 6 | 1 | 160 |
Flexural stiffness 1 (d-i) | 3.5 | 5 | 1 | 80 |
Flexural stiffness 2 (d-ii) | 3.5 | 5 | 1 | 200 |
Flexural stiffness 3 (d-iii) | 3.5 | 5 | 1 | 320 |
Parameters | Condition 1 | Condition 2 |
---|---|---|
Length l/m | 0.8 | 1 |
Mass m/kg | 0.8 | 1.1 |
Flexural rigidity EI/Nm2 | 400 | 400 |
Coulomb friction torque Fc/Nm | 0.28 | 0.28 |
Static friction torque Fs/Nm | 0.34 | 0.34 |
Low-pass filter parameters α | 0.1 | 0.1 |
Low-pass filter parameters β | 0.1 | 0.1 |
Low-pass filter parameters γ | 0.1 | 0.1 |
Controller parameters KP | 20 | 20 |
Controller parameters KI | 5 | 5 |
Parameters | Condition 1 | Condition 2 | Condition 3 |
---|---|---|---|
Length l/m | 3 | 3.5 | 4 |
Mass m/kg | 2 | 2 | 2 |
Flexural rigidity EI/Nm2 | 50 | 50 | 50 |
Low-pass filter parameters α | 0.1 | 0.1 | 0.1 |
Low-pass filter parameters β | 0.1 | 0.1 | 0.1 |
Low-pass filter parameters γ | 0.1 | 0.1 | 0.1 |
Controller parameters KP | 10 | 10 | 10 |
Controller parameters KI | 5 | 5 | 5 |
Control Strategy | Means of Absolute Error | Variance of Error | Standard Deviation of Error | |
---|---|---|---|---|
Condition 1 | PI | 0.1587 | 0.0221 | 0.149 |
PI + DOB | 0.1406 | 0.0145 | 0.121 | |
FCPI + DOB | 0.1253 | 0.0133 | 0.115 | |
Condition 2 | PI | 0.1626 | 0.0232 | 0.152 |
PI + DOB | 0.1497 | 0.0195 | 0.139 | |
FCPI + DOB | 0.1428 | 0.0152 | 0.123 | |
Condition 2 | PI | 0.1706 | 0.0424 | 0.206 |
PI + DOB | 0.1643 | 0.0308 | 0.175 | |
FCPI + DOB | 0.1462 | 0.0267 | 0.166 |
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Liu, J.; Li, X.; Yin, M.; Wei, L.; Wang, H. Modeling and Rotation Control Strategy for Space Planar Flexible Robotic Arm Based on Fuzzy Adjustment and Disturbance Observer. Mathematics 2024, 12, 2513. https://doi.org/10.3390/math12162513
Liu J, Li X, Yin M, Wei L, Wang H. Modeling and Rotation Control Strategy for Space Planar Flexible Robotic Arm Based on Fuzzy Adjustment and Disturbance Observer. Mathematics. 2024; 12(16):2513. https://doi.org/10.3390/math12162513
Chicago/Turabian StyleLiu, Jiaqi, Xiaopeng Li, Meng Yin, Lai Wei, and Haozhe Wang. 2024. "Modeling and Rotation Control Strategy for Space Planar Flexible Robotic Arm Based on Fuzzy Adjustment and Disturbance Observer" Mathematics 12, no. 16: 2513. https://doi.org/10.3390/math12162513