Experimental Implementation of Tracking Error Elimination for Omnidirectional Wheelchair Using PD-Fuzzy-P Controller
Wheelchairs have been an active-research problem in the maneuverability of mobile robots over the past decade. This study aims to develop the transportability of disabled people by controlling the motion of their smart wheelchairs. It presents a design of omnidirectional mobile robot where its wheels can be equipped to replace a conventional electric wheelchair in order to achieve flexible and reliable maneuverability. The decentralized algorithm is used for motion control of the omnidirectional robot, which deals with the three independent components of robot’s motion in the body coordinate frame: rotational moving, horizontal moving and vertical moving, which can be controlled separately with separated and different sub-controllers. The simulation analysis of the proposed study has been tested in authors’ previous work and two approaches of artificial intelligent-based controllers (PD-Fuzzy-P and GA-PID controllers) have been built in order to control optimally the maneuverability of such system. The results have showed that the PD-fuzzy-P controller has converged faster than the GA-PID controller and the robot has been able to track successfully the sharp curves’ maneuverability, such as a 90° corner in the squared shape and a U-turn in the rose shape with an error approaching zero. In this paper, the experimental tests of the PD-fuzzy-P controller are carried out on a real robot developed using EV3 Lego kit parts and Vicon motion capturing system is used to capture the robot’s motion in various trajectory scenarios in order to test the effectiveness of the proposed control design.
Copyright © 2021 Praise Worthy Prize - All rights reserved.
Gibson, C.; Turner, S.; Donnelly, M. One degree of Separation: Paralysis and Spinal Cord Injury in the United States; Christopher and Dana Reeve Foundation: Short Hills, NJ, USA, 2009.
Madarasz, R.; Heiny, L.; Cromp, R.; & Mazur, N. The design of an autonomous vehicle for the disabled. IEEE Journal on Robotics and Automation, 1986, 2(3), 117-126.
Kundu, A. S.; Mazumder, O.; Lenka, P. K.; & Bhaumik, S. Design and Performance Evaluation of 4 Wheeled Omni Wheelchair with Reduced Slip and Vibration. Procedia Computer Science, 2017, 105, 289–295.
Yang, B.; & Xi, L. Development of an Omni-Directional Wheelchair Robot. International Conference on Engineering Simulation and Intelligent Control (ESAIC). 2018.
Cui, R.; Li, Y.; & Yan, W. Mutual Information-Based Multi-AUV Path Planning for Scalar Field Sampling Using Multidimensional RRT*. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016, 46(7), 993–1004.
Li, W.; Yang, C.; Jiang, Y.; Liu, X.; & Su, C.-Y. Motion Planning for Omnidirectional Wheeled Mobile Robot by Potential Field Method. Journal of Advanced Transportation, 2017, 1–11.
Kim, C.; Suh, J.; & Han, J.-H. Development of a Hybrid Path Planning Algorithm and a Bio-Inspired Control for an Omni-Wheel Mobile Robot. Sensors, 2020, 20(15), 4258.
Loubar, H., Boushaki, R., Aouati, A., Bouanzoul, M., Sliding Mode Controller for Linear and Nonlinear Trajectory Tracking of a Quadrotor, (2020) International Review of Automatic Control (IREACO), 13 (3), pp. 128-138.
Watanabe K., Shiraishi Y., Tzafestas S. G., Tang J., and Fukuda T. Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots, Journal of Intelligent and Robotic Systems, 1998, 22(3-4), 315-330.
Liu Y.; Zhu J.J; Williams II R.L.; Wu J. Omni-directional mobile robot controller based on trajectory linearization. Robotics and Autonomous Systems, 2008, 56, 461–479.
Abiyev; Rahib H.; Irfan S. Günsel; et al. Fuzzy Control of Omnidirectional Robot. Procedia Computer Science, 2017,120, 608–16.
Hacene, N.; & Mendil, B. Motion Analysis and Control of Three-Wheeled Omnidirectional Mobile Robot. Journal of Control, Automation and Electrical Systems, 2019, 30(2), 194–213.
George, R., Hasanien, H., Al-Durra, A., Badr, M., Model Predictive Controller for Performance Enhancement of Automatic Voltage Regulator System, (2018) International Journal on Energy Conversion (IRECON), 6 (6), pp. 208-217.
Chen, Y. et al. Research on UAV Flight Tracking Control Based on Genetic Algorithm optimization and Improved bp Neural Network pid Control. 2019 Chinese Automation Congress (CAC).
Besarati, S., Atashkari, K., Hajiloo, A., Nariman-zadeh, N., Nikpey, H., Multi-Objective Pareto Robust Design of PID Controllers for Variable Compression Ratio Engines Using Genetic Algorithms, (2018) International Journal on Engineering Applications (IREA), 6 (6), pp. 211-220.
Prada, G., Rojas, J., Romero, G., Fuzzy Adaptive PID Control of a Shell and Tube Heat Exchanger Output Temperature, (2020) International Review of Automatic Control (IREACO), 13 (6), pp. 283-291.
Tzafestas, S.; & Papanikolopoulos, N. P. Incremental fuzzy expert PID control. IEEE Transactions on Industrial Electronics, 1990, 37(5), 365–371.
Abiyev, R. H.; Akkaya, N.; Aytac, E.; Günsel, I.; & Çağman, A. Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks. BioMed Research International, 2016, 1–9.
Ng, D. W.-K.; Soh, Y.-W.; & Goh, S.-Y. Development of an Autonomous BCI Wheelchair. 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces (CIBCI).
Li, Z., Xiong, Y., & Zhou, L. ROS-Based Indoor Autonomous Exploration and Navigation Wheelchair. 2017 10th International Symposium on Computational Intelligence and Design (ISCID). doi:10.1109/iscid.2017.55
He, S.; Zhang, R.; Wang, Q.; Chen, Y.; Yang, T.; Feng, Z.; … Li, Y. A P300-Based Threshold-Free Brain Switch and Its Application in Wheelchair Control. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 25(6), 715–725.
Batayneh, WM, Hatamleh, KS, Nusayr, AA, Alquraan, R, Al-Khaleel, A, & Batainah, A. Low-Cost Wi-Fi Navigation of Smart Wheelchairs. Proceedings of the ASME 2018 International Mechanical Engineering Congress and Exposition. Volume 13: Design, Reliability, Safety, and Risk. Pittsburgh, Pennsylvania, USA. November 9–15, 2018. V013T05A054. ASME.
Bui, T. L. Decentralized Motion Control for Omnidirectional Mobile Platform-Tracking a Trajectory Using PD Fuzzy Controller. Lecture Notes in Electrical Engineering, 2016, 803–819.
Batayneh, W.; & AbuRmaileh, Y. Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers. Sensors. 2020, 20(12), 3525.
Zadeh, L.A. Fuzzy Sets. Inf. Control 1965, 8, 338–353.
Vicon virtual production. Retrieved from: https://www.vicon.com
Oladipo, S., Sun, Y., Wang, Z., Optimization of PID Controller with Metaheuristic Algorithms for DC Motor Drives: Review, (2020) International Review of Electrical Engineering (IREE), 15 (5), pp. 352-381.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2021 Praise Worthy Prize