Coupling Control Strategy and Experiments for Motion Mode Switching of a Novel Electric Chassis
Source abstract
Abstract
A flexible chassis (FC) is a type of electric vehicle driven by in-wheel motors that can be used in narrow conditions in agricultural facilities. The FC is composed primarily of four off-center steering mechanisms (OSMs) that can be controlled independently. Various FC operation modes can be achieved including cross motion (CM), in-place rotation (IR), diagonal motion (DM), and steering motion (SM). However, it is difficult to achieve satisfactory motion mode switching (MMS) results under traditional distribution control methodologies due to a lack of linkage relationships between the four OSMs. The goal of this study was to provide a coupling control method that can cope with this problem. First, dynamic MMS models were derived. Then, an MMS coupling error (CE) model was derived based on coupling control and Lyapunov stability theory. Second, a fuzzy proportional integral derivative (PID) controller with self-tuning parameters was designed to reduce the CE during MMS. A fuzzy PI controller was also employed to improve response times and decrease OSM tracking motion steady-state error. Finally, MATLAB/Simulink simulations were performed and experimentally validated on hard pavement. The results showed that the proposed methodology could effectively reduce CE and guarantee MMS control stability while substantially shortening response times. The proposed methodology is effective and feasible for FC MMS.
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Research context
OpenAlex topics: Vehicle Dynamics and Control Systems · Soil Mechanics and Vehicle Dynamics · Mechanical Engineering and Vibrations Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Shaanxi Engineering Research Centre for Agriculture Equipment, Yangling 712100, China
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan
College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi’an 710119, China
Funding
National Natural Science Foundation of China
References (42)
Show source-provided references
1. A high temporal-spatial resolution air pollutant emission inventory for agricultural machinery in China10.1016/j.jclepro.2018.02.120 ↗
2. Autonomous greenhouse mobile robot driving strategies from system integration perspective: Review and application10.1109/TMECH.2014.2350433 ↗
3. Exhaust gases emissions from agricultural tractors: State of the art and future perspectives for machinery operators10.1016/j.biosystemseng.2019.07.011 ↗
4. Reducing air pollution with hybrid-powered robotic tractors for precision agriculture10.1016/j.biosystemseng.2016.01.008 ↗
5. Agricultural robots for field operations: Concepts and components10.1016/j.biosystemseng.2016.06.014 ↗
6. Two-stage guidance control scheme for high-precision straight-line navigation of a four-wheeled planting robot in a greenhouse10.13031/trans.59.11801 ↗
7. Ambient awareness for agricultural robotic vehicles10.1016/j.biosystemseng.2015.12.010 ↗
8. Electronic stability control for electric vehicle with four in-wheel motors10.1007/s12239-014-0060-4 ↗
9. Lateral stability control of in-wheel-motor-driven electric vehicles based on sideslip angle estimation using lateral tire force sensors10.1109/TVT.2012.2191627 ↗
10. State of the art of autonomous agricultural off-road vehicles driven by renewable energy systems10.1016/j.egypro.2019.04.002 ↗
11. Wang, Z., Wang, Y., Zhang, L., and Liu, M. (2017). Vehicle stability enhancement through hierarchical control for a four-wheel-independently-actuated electric vehicle. Energies, 10.10.3390/en10070947 ↗
12. Zhai, L., Hou, R., Sun, T., and Kavuma, S. (2018). Continuous steering stability control based on an energy-saving torque distribution algorithm for a four in-wheel-motor independent-drive electric vehicle. Energies, 11.10.3390/en11020350 ↗
13. Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method10.1016/j.jfranklin.2014.03.015 ↗
14. Stable and robust vehicle steering control using an overhead guide in greenhouse tasks10.1016/j.compag.2015.12.019 ↗
15. Robust navigation control of a 4WD/4WS agricultural robotic vehicle10.1016/j.compag.2019.104892 ↗
16. Design and implementation of fuzzy logic controller for online computer controlled steering system for navigation of a teleoperated agricultural vehicle10.1155/2013/590861 ↗
17. A human centred design of general purpose unmanned electric vehicle chassis for agriculture task payload10.1115/1.4034740 ↗
18. Extended Ackerman Steering Principle for the coordinated movement control of a four wheel drive agricultural mobile robot10.1016/j.compag.2018.06.036 ↗
19. Development of a tomato harvesting robot used in greenhouse
20. Thorvald II—A modular and re-configurable agricultural robot10.1016/j.ifacol.2017.08.1005 ↗
21. Speed-dependent coordinated control of differential and assisted steering for in-wheel motor driven electric vehicles
22. Decoupling control of steering and driving system for in-wheel-motor-drive electric vehicle10.1016/j.ymssp.2017.08.042 ↗
23. Mechatronic design of a four wheel steering mobile robot with fault-tolerant odometry feedback
24. Decoupling control of vehicle chassis system based on neural network inverse system10.1016/j.ymssp.2017.12.032 ↗
25. Torque distribution algorithm for an independently driven electric vehicle using a fuzzy control method10.3390/en8088537 ↗
26. Performance of fractional PID algorithms controlling nonlinear systems with saturation and backlash phenomena10.1177/1077546307077499 ↗
27. An augmented system approach for LMI-based control design of constrained Takagi-Sugeno fuzzy systems10.1016/j.engappai.2016.11.011 ↗
28. Fuzzy steering control for autonomous vehicles under actuator saturation: Design and experiments10.1016/j.jfranklin.2017.11.027 ↗
29. Perng, J.W., and Lai, Y.H. (2016). Robust longitudinal speed control of hybrid electric vehicles with a two-degree- of-freedom fuzzy logic controller. Energies, 9.10.3390/en9040290 ↗
30. Lateral control of autonomous vehicles based on fuzzy logic10.1016/j.conengprac.2014.09.015 ↗
31. Fuzzy control method for a steering system consisting of a four-wheel individual steering and four-wheel individual drive electric chassis
32. Design and test of flexible chassis automatic tracking steering system
33. Development and validation of a method for approximating road surface texture-induced contact pressure in tire-pavement interaction10.2346/1.2148796 ↗
34. Vo, A.T., and Kang, H.J. (2018). An Adaptive Neural Non-Singular Fast-Terminal Sliding-Mode Control for Industrial Robotic Manipulators. Appl. Sci., 8.10.3390/app8122562 ↗
35. A Lyapunov’s direct method for the global robust stabilization of nonlinear cascaded systems10.1016/j.automatica.2007.06.027 ↗
36. Rodriguez, J., Herman, C., and Gordillo, J.L. (2019). Design of an Adaptive Sliding Mode Control for a Micro-AUV Subject to Water Currents and Parametric Uncertainties. J. Mar. Sci. Eng., 7.10.3390/jmse7120445 ↗
37. Kumar, N.S., Sadasivam, V., and Prema, K. (2004, January 21–24). Design and Simulation of Fuzzy Controller for Closed Loop Control of Chopper Fed Embedded DC Drives. Proceedings of the IEEE international conference, Singapore.
38. Nguyen, A.T., Sentouh, C., Zhang, H., and Popieul, J.C. (2019). Fuzzy Static Output Feedback Control for Path Following of Autonomous Vehicles with Transient Performance Improvements. IEEE Trans. Intell. Transp. Syst., 1–11.
39. Using fuzzy logic in automated vehicle control10.1109/MIS.2007.18 ↗
40. Experiment and optimization of mode switching controlling parameters for agricultural flexible chassis
41. PI, PD and PID Controllers Using Single DVCCTA10.1007/s40998-019-00180-z ↗
42. A tuning strategy for multivariable PI and PID controllers using differential evolution combined with chaotic Zaslavskii map