INDIRECT ADAPTIVE CONTROL BASED ON FUZZY INFERENCE SYSTEMS FOR WHEEL VEHICLES WITH MODEL UNCERTAINTY AND UNKNOWN DISTURBANCE | Mai | TNU Journal of Science and Technology

INDIRECT ADAPTIVE CONTROL BASED ON FUZZY INFERENCE SYSTEMS FOR WHEEL VEHICLES WITH MODEL UNCERTAINTY AND UNKNOWN DISTURBANCE

About this article

Received: 07/03/25                Revised: 04/06/25                Published: 04/06/25

Authors

1. Do Thi Mai, School of Electrical and Electronic Engineering - Ha Noi University of Science and Technology
2. Pham Luong Hoang, School of Electrical and Electronic Engineering - Ha Noi University of Science and Technology
3. Nguyen Thi Hong Hanh, Institute of Mechanics - Viet Nam Academy of Science and Technology
4. Nguyen Hoai Nam Email to author, School of Electrical and Electronic Engineering - Ha Noi University of Science and Technology

Abstract


In this paper, an indirect adaptive controller based on fuzzy inference systems for a three-wheeled mobile robot was designed. The mathematical model of the non-holonomic mobile robots was considered with uncertain parameters and matched external disturbances, whichwas combined into an unknown lumped dynamic functions. These unknown functions were approximated by using fuzzy inference systems with adaptive tuning laws. Based on the approximate results obtained from the fuzzy inference system, the control signal for the inner loop control was calculated to ensure the convergence of the speed error to the origin region. Numerical simulations were performed on MATLAB when the robot was affected by time-varying unknown parameters and matched disturbances. The numerical simulation results show that the trajectory tracking error approaches the origin domain in short time and proves the high capacity of the fuzzy inference system to approximate the nonlinear functions and the effectiveness of the proposed control method.

Keywords


Autonomous vehicle; Adaptive control; Model uncertainty; Unknown matched disturbance; Fuzzy inference system

References


[1] T. M. Do and H. N. Nguyen, “Path tracking control approach and processing lumped disturbances for AGV in recent years: an Overview,” in Proc. the 2nd International Conference ICTA 2023, Thai Nguyen (Viet Nam), 2023, pp. 180-198.

[2] K. Yasmine, B. Mohamed, and D. Tarak, “Adaptive sliding mode control for trajectory tracking of nonholonomic mobile robot with uncertain kinematics and dynamics,” Applied Artificial Intelligence, vol. 32, no. 9, pp. 924-938, 2018.

[3] B. Moudoud, H. Aissaoui, and M. Diany, “Robust adaptive trajectory tracking control based on sliding mode of electrical wheeled mobile robot,” International Journal of Mechanical Engineering and Robotics Research, vol. 10, no. 9, pp. 505-509, 2021.

[4] M. Brahim, A. Hicham, and D. Mohammed, “Extended state observer-based finite-time adaptive sliding mode control for wheeled mobile robot,” Journal of Control and Decision, vol. 9, no. 4, pp. 465-476, 2022.

[5] Y. Guo, L. Yu, and J. Xu, “Robust finite-time trajectory tracking control of wheeled mobile robots with parametric uncertainties and disturbances,” J. Syst. Sci. Complex, vol. 32, no. 5, pp. 1358–1374, 2019.

[6] G. K. Tran, H. N. Nguyen, and D. P. Nguyen, “Observer-based controllers for two-wheeled inverted robots with unknown input disturbance and model uncertainty,” Journal of Control Science and Engineering, vol. 2020, no. 1, pp. 1-12, 2020.

[7] D. P. Nguyen and H. N. Nguyen, “A simple approach to estimate unmatched disturbances for nonlinear nonautonomous systems,” Int. J. Robust Nonlinear Control, vol. 32, no. 17, pp. 9160–9173, 2022.

[8] J. K. Taheri and M. J. Khosrowjerdi, “Adaptive trajectory tracking control of wheeled mobile robots with disturbance observer,” Int. J. Adapt. Control Signal Process, vol. 28, no. 1, pp. 14-27, 2014.

[9] N. T. T. Vu, X. L. Ong, N. H. Trinh, and S. T. H. Pham, “Robust adaptive controller for wheel mobile robot with disturbances and wheel slips,” International Journal of Electrical and Computer Engineering (IJECE), vol. 11, no. 1, pp. 336-346, 2021.

[10] L. Li, W. Tianqi, X. Yuanqing, and Z. Ning, “Trajectory tracking control for wheeled mobile robots based on nonlinear disturbance observer with extended Kalman filter,” Journal of the Franklin Institute, vol. 357, no. 13, pp. 8491-8507, 2020.

[11] M. Yue, L. Wang, and T. Ma, “Neural network based terminal sliding mode control for wmrs affected by an augmented ground friction with slippage effect,” IEEE/CAA Journal of Automatica Sinica, vol. 4, no. 3, pp. 498–506, 2017.

[12] Z. Chen, Y. Liu, W. He, H. Qiao, and H. Ji, “Adaptive-neural-network-based trajectory tracking control for a nonholonomic wheeled mobile robot with velocity constraints,” IEEE Transactions on Industrial Electronics, vol. 68, no. 6, pp. 5057–5067, 2020.

[13] Y. Wu and Y. Wang, “Asymptotic tracking control of uncertain nonholonomic wheeled mobile robot with actuator saturation and external disturbances,” Neural Computing and Applications, vol. 32, no. 12, pp. 8735–8745, 2020.

[14] N. T. T. Vu, N. P. Tran, and N. H. Nguyen, “Adaptive Neuro‐Fuzzy Inference System Based Path Planning for Excavator Arm,” Journal of Robotics, vol. 2018, no. 1, pp. 1-7, 2018.

[15] D. Chwa, “Fuzzy adaptive tracking control of wheeled mobile robots with state-dependent kinematic and dynamic disturbances,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 3, pp. 587–593, 2011.

[16] S. Peng and W. Shi, “Adaptive fuzzy integral terminal sliding mode control of a nonholonomic wheeled mobile robot,” Mathematical Problems in Engineering, vol. 2017, no. 1, 2017, Art. no. 3671846.

[17] H. Ying, “General SISO Takagi-Sugeno fuzzy systems with linear rule consequent are universal approximators,” IEEE Transactions on Fuzzy Systems, vol. 6, no. 4, pp. 582 – 587, 1998.

[18] H. Ying, “Sufficient conditions on uniform approximation of multivariate functions by general Takagi-Sugeno fuzzy systems with linear rule consequent," IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Umans, vol. 28, no.4, pp. 515 –520, 1998.




DOI: https://doi.org/10.34238/tnu-jst.12238

Refbacks

  • There are currently no refbacks.
TNU Journal of Science and Technology
Rooms 408, 409 - Administration Building - Thai Nguyen University
Tan Thinh Ward - Thai Nguyen City
Phone: (+84) 208 3840 288 - E-mail: jst@tnu.edu.vn
Based on Open Journal Systems
©2018 All Rights Reserved