Motion Control of a Mobile Robot Using the Hedge-Algebras-Based Controller

被引:4
作者
Nguyen, Sy-Tai [1 ,2 ]
Mac, Thi-Thoa [1 ,3 ]
Bui, Hai-Le [1 ,3 ]
机构
[1] Hanoi Univ Sci & Technol, Sch Mech Engn, 1 Dai Co Viet St, Hanoi, Vietnam
[2] Viet Nam Natl Inst Occupat Safety & Hlth, Hanoi, Vietnam
[3] Hanoi Univ Sci & Technol, Sch Mech Engn, Intelligent Mechatron & AI Res Grp, 1 Dai Co Viet St, Hanoi, Vietnam
关键词
FUZZY CONTROL; ALGORITHM; NAVIGATION;
D O I
10.1155/2023/6613293
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Hedge-algebras (HA) theory provides a useful mathematical tool for modeling the linguistic values of a linguistic variable. These values are quantified by real numbers between 0 and 1. Therefore, the HA-based controller (HAC) has many advantages over the traditional fuzzy set theory-based controller (FC) in setup steps, control efficiency, computation time, and optimization. This study aims to control the avoidance of obstacles in the workspace and move to the destination of an autonomous robot using HAC, in which the HAC is optimized using the balancing composite motion optimization (BCMO) to return the optimal path. In which the investigated model is inherited from a reference. The HAC is established and optimized to minimize the traveling distance of the mobile robot and help it to avoid obstacles simultaneously. Simulations include one and two obstacle environments. Design variables, when optimizing, include the fuzzy parameters of linguistic variables and the reference range of state variables. This work is the first study in motion control of mobile robots based on the HA theory. The simulation data show that the proposed control rule base suits the mobile robot models. Therefore, the control efficiency of HAC is higher than that of a FC both in terms of the traveling distance of the robot and computation time (CPU time). Also, the establishment steps of the HAC controller show that HAC is more explicit, easier to optimize, and simpler to operate than FC. Research results in the present work also indicate that HAC can be developed and applied in motion control problems for different robot models with the advantages of a smaller traveling distance and faster computation time.
引用
收藏
页数:13
相关论文
共 50 条
[41]   PSO-based motion fuzzy controller design for mobile robots [J].
Wong, Ching-Chang ;
Wang, Hou-Yi ;
Li, Shih-An .
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2008, 10 (01) :24-32
[42]   IWO-based adaptive neuro-fuzzy controller for mobile robot navigation in cluttered environments [J].
Parhi, Dayal R. ;
Mohanty, Prases K. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 83 (9-12) :1607-1625
[43]   Using an Adaptive Fuzzy Neural Network Based on a Multi-Strategy-Based Artificial Bee Colony for Mobile Robot Control [J].
Chen, Cheng-Hung ;
Jeng, Shiou-Yun ;
Lin, Cheng-Jian .
MATHEMATICS, 2020, 8 (08)
[44]   Reactive control using behavior modelling of a mobile robot [J].
Ayari, Imen ;
Chatti, Abderrazak .
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2007, 2 (03) :217-228
[45]   AUTONOMOUS CONTROL OF A MOBILE ROBOT USING ENVIRONMENT INFORMATION [J].
KOMORIYA, K ;
TANI, K ;
SHIRAI, N ;
OYAMA, E .
JOURNAL OF MECHANICAL ENGINEERING LABORATORY, 1992, 46 (02) :186-210
[46]   Inverted Pendulum Control Using Fuzzy Reasoning Method Based on Hedge Algebras by Approach to Semantic Quantifying Adjustment of Linguistic Value [J].
Nguyen Duy Minh ;
Do Thi Mai ;
Nguyen Thi Thu Hien .
ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGY, 2017, 538 :312-321
[47]   Vision-Based Guidance and Switching-Based Sliding Mode Controller for a Mobile Robot in the Cyber Physical Framework [J].
Singh, Padmini ;
Agrawal, Pooja ;
Karki, Hamad ;
Shukla, Amit ;
Verma, Nishchal K. ;
Behera, Laxmidhar .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (04) :1985-1997
[48]   Navigation and Control System of Mobile Robot Based on ROS [J].
Zhi, Li ;
Mei Xuesong .
PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018), 2018, :368-372
[49]   Laboratory Course on Navigation and Motion Control of the Mobile Robot with the Differential Drive of Wheels [J].
Kolker, Alexey B. ;
Pershina, Zhanna S. .
2016 13TH INTERNATIONAL SCIENTIFIC-TECHNICAL CONFERENCE ON ACTUAL PROBLEMS OF ELECTRONIC INSTRUMENT ENGINEERING (APEIE), VOL 1, 2016, :357-360
[50]   A PATH-GENERATING MOTION CONTROL SCHEME FOR A MOBILE ROBOT IN THE ENVIRONMENT OF OBSTACLES [J].
Lee, Ho-Hoon .
PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2018, VOL 4A, 2019,