Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance
Abstract
:1. Introduction
2. Materials and Methods
2.1. Test Prototype
2.2. Path-Tracking Method Design
2.2.1. Pure Pursuit Model
2.2.2. Kinematics Equation of the Vehicle
2.2.3. Design of Fuzzy Controller
- (1)
- Membership Function
- (2)
- Control Rules
3. Results
3.1. Path-Tracking Test Design
3.2. Test Results
4. Discussion
4.1. Path-Tracking Accuracy
4.2. Convergence Rapidity
4.3. Path-Tracking Stability
5. Conclusions
- (1)
- To further improve the path-tracking quality of automatic navigation in agricultural machinery with a 4WIS–4WID structure, a pure pursuit model based on a variable look-ahead distance was adopted. A fuzzy controller was designed, with lateral deviation and heading deviation as the input and look-ahead distance as the output, to obtain dynamic variable look-ahead distances. A real vehicle path-tracking test was implemented in a real agricultural environment to validate the effectiveness of the algorithm in path tracking.
- (2)
- The dynamic adjustment of the variable look-ahead distance according to the deviation of the vehicle matches the driving habits of experienced drivers. The non-uniform membership function quantization method can guarantee the accuracy of path tracking and consider the speed and stability of the path tracking. Compared with the fixed look-ahead distance method, the method presented in this paper improved the performance of average deviation, average steady-state deviation, average steady-state distance, average maximal deviation, and the average stability time by 19.6%, 24.4%, 33.7%, 2.9% and 20.3%, respectively, according to the comparison test of the test prototype. The path-tracking accuracy, convergence rapidity, and stability were significantly improved compared to those of the traditional fixed look-ahead distance method. The path-tracking method can be applied to multi-input, nonlinear and time-varying system control.
- (3)
- The quantitative scale design of fuzzy control rules can be further refined. In follow-up research, more fine fuzzy control rules can be used, and the input and output variables can be quantified into more fuzzy subsets to determine a variety of deviation states with more accurate look-ahead distances, further improving the path-tracking accuracy of automatic navigation technology for agricultural machinery.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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LD | θ | |||||
---|---|---|---|---|---|---|
NB | NS | ZO | PS | PB | ||
d | NB | NB | NB | NS | ZO | PS |
NS | NS | NS | ZO | PS | PS | |
ZO | ZO | PS | PB | PS | ZO | |
PS | PS | PS | ZO | NS | NS | |
PB | PS | ZO | NS | NB | NB |
Initial States | Look-Ahead Distance (m) | Average Deviation (cm) | Stability Distance (cm) | Maximum Deviation (cm) | Stability Time (s) | Steady-State Deviation (cm) | Standard Deviation of the Steady-State Deviation (cm) |
---|---|---|---|---|---|---|---|
(1 m,−90°) | Ldynamic | 12.5 | 64.6 | 100.0 | 3.2 | 2.0 | 1.3 |
Lfixed | 17.5 | 274.7 | 100.0 | 5.6 | 3.4 | 2.1 | |
(1 m, 0°) | Ldynamic | 20.8 | 204.9 | 106.8 | 4.2 | 3.4 | 0.9 |
Lfixed | 21.7 | 275.5 | 107.9 | 5.2 | 4.4 | 1.5 | |
(0 m, 90°) | Ldynamic | 25.7 | 342.3 | 100.9 | 7.8 | 3.8 | 1.6 |
Lfixed | 34.2 | 372.9 | 109.1 | 8.4 | 4.6 | 1.9 |
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Xu, L.; Yang, Y.; Chen, Q.; Fu, F.; Yang, B.; Yao, L. Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance. Appl. Sci. 2022, 12, 8651. https://doi.org/10.3390/app12178651
Xu L, Yang Y, Chen Q, Fu F, Yang B, Yao L. Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance. Applied Sciences. 2022; 12(17):8651. https://doi.org/10.3390/app12178651
Chicago/Turabian StyleXu, Lijun, Yankun Yang, Qinhan Chen, Fengcheng Fu, Bihang Yang, and Lijian Yao. 2022. "Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance" Applied Sciences 12, no. 17: 8651. https://doi.org/10.3390/app12178651
APA StyleXu, L., Yang, Y., Chen, Q., Fu, F., Yang, B., & Yao, L. (2022). Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance. Applied Sciences, 12(17), 8651. https://doi.org/10.3390/app12178651