Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot
We develop a new robust control scheme for a non-holonomic spherical robot. To this end, the mathematical model of a pendulum driven non-holonomic spherical robot is first presented. Then, a recurrent neural network-based robust nonsingular sliding mode control is proposed for stabilization and trac...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9222023/ |
| _version_ | 1818734605899923456 |
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| author | Shu-Bo Chen Alireza Beigi Amin Yousefpour Farhad Rajaee Hadi Jahanshahi Stelios Bekiros Raul Alcaraz Martinez Yuming Chu |
| author_facet | Shu-Bo Chen Alireza Beigi Amin Yousefpour Farhad Rajaee Hadi Jahanshahi Stelios Bekiros Raul Alcaraz Martinez Yuming Chu |
| author_sort | Shu-Bo Chen |
| collection | DOAJ |
| description | We develop a new robust control scheme for a non-holonomic spherical robot. To this end, the mathematical model of a pendulum driven non-holonomic spherical robot is first presented. Then, a recurrent neural network-based robust nonsingular sliding mode control is proposed for stabilization and tracking control of the system. The designed recurrent neural network is applied to approximate compound disturbances, including external interferences and dynamic uncertainties. Moreover, the controller is designed in a way that avoids the singularity problem in the system. Another advantage of the proposed scheme is its ability for tracking control while there exists control input saturation, which is a serious concern in robotic systems. Based on the Lyapunov theorem, the stability of the closed-loop system has also been confirmed. Lastly, the performance of the proposed control technique for the uncertain system in the presence of an external disturbance, unknown input saturation, and dynamic uncertainties has been investigated. Also, the proposed controller has been compared with a Fuzzy-PID one. Simulation results show the effectiveness and superiority of the developed control technique. |
| first_indexed | 2024-12-18T00:08:01Z |
| format | Article |
| id | doaj.art-db344d0fc8b2497492785281e4a811b1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T00:08:01Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-db344d0fc8b2497492785281e4a811b12022-12-21T21:27:45ZengIEEEIEEE Access2169-35362020-01-01818844118845310.1109/ACCESS.2020.30307759222023Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical RobotShu-Bo Chen0Alireza Beigi1https://orcid.org/0000-0002-9980-5663Amin Yousefpour2https://orcid.org/0000-0002-6168-9441Farhad Rajaee3Hadi Jahanshahi4https://orcid.org/0000-0001-7810-6479Stelios Bekiros5Raul Alcaraz Martinez6https://orcid.org/0000-0002-0942-3638Yuming Chu7https://orcid.org/0000-0002-0944-2134School of Science, Hunan City University, Yiyang, ChinaSchool of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, IranDepartment of Mechatronics Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, IranDepartment of Mechanical Engineering, University of Manitoba, Winnipeg, MB, CanadaDepartment of Economics, European University Institute, Florence, ItalyResearch Group in Electronic, Biomedical, and Telecommunication Engineering, University of Castilla-La Mancha (UCLM), Cuenca, SpainDepartment of Mathematics, Huzhou University, Huzhou, ChinaWe develop a new robust control scheme for a non-holonomic spherical robot. To this end, the mathematical model of a pendulum driven non-holonomic spherical robot is first presented. Then, a recurrent neural network-based robust nonsingular sliding mode control is proposed for stabilization and tracking control of the system. The designed recurrent neural network is applied to approximate compound disturbances, including external interferences and dynamic uncertainties. Moreover, the controller is designed in a way that avoids the singularity problem in the system. Another advantage of the proposed scheme is its ability for tracking control while there exists control input saturation, which is a serious concern in robotic systems. Based on the Lyapunov theorem, the stability of the closed-loop system has also been confirmed. Lastly, the performance of the proposed control technique for the uncertain system in the presence of an external disturbance, unknown input saturation, and dynamic uncertainties has been investigated. Also, the proposed controller has been compared with a Fuzzy-PID one. Simulation results show the effectiveness and superiority of the developed control technique.https://ieeexplore.ieee.org/document/9222023/Spherical robotsliding mode controlrecurrent neural networkexternal disturbanceunknown input saturationcontrol singularity |
| spellingShingle | Shu-Bo Chen Alireza Beigi Amin Yousefpour Farhad Rajaee Hadi Jahanshahi Stelios Bekiros Raul Alcaraz Martinez Yuming Chu Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot IEEE Access Spherical robot sliding mode control recurrent neural network external disturbance unknown input saturation control singularity |
| title | Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot |
| title_full | Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot |
| title_fullStr | Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot |
| title_full_unstemmed | Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot |
| title_short | Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot |
| title_sort | recurrent neural network based robust nonsingular sliding mode control with input saturation for a non holonomic spherical robot |
| topic | Spherical robot sliding mode control recurrent neural network external disturbance unknown input saturation control singularity |
| url | https://ieeexplore.ieee.org/document/9222023/ |
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