Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators
In this article, a hybrid control approach combining sliding mode and H-infinity is proposed for an uncertain single-link flexible manipulator. The sliding mode controller stabilizes the nonlinear manipulator system, while the H-infinity controller enhances the noise rejection capability of the syst...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9195856/ |
| _version_ | 1830297700824776704 |
|---|---|
| author | Behrouz Kharabian Hossein Mirinejad |
| author_facet | Behrouz Kharabian Hossein Mirinejad |
| author_sort | Behrouz Kharabian |
| collection | DOAJ |
| description | In this article, a hybrid control approach combining sliding mode and H-infinity is proposed for an uncertain single-link flexible manipulator. The sliding mode controller stabilizes the nonlinear manipulator system, while the H-infinity controller enhances the noise rejection capability of the system by reducing the total system nonlinearity. The proposed hybrid controller is designed with the goal of rejecting external noises, hence providing a higher system performance, compared to a pure sliding mode controller. To avoid unintentional consequences of switching between the sliding mode and H-infinity controller, a fuzzy neural network weighting method is designed providing a smooth synthesis of both controller outputs. The neuro-fuzzy method applies a weighted combination of the two controller outputs to the manipulator system. In addition, a novel fuzzy estimation method is used to characterize the unstructured nonlinear disturbances in manipulator systems. The proposed hybrid control approach along with the fuzzy estimator is capable of providing a versatile means to stabilize flexible manipulator systems while maintaining a precise reference trajectory tracking in presence of unstructured uncertainty and nonlinear dynamics, as demonstrated by simulation results. |
| first_indexed | 2024-12-19T07:37:57Z |
| format | Article |
| id | doaj.art-231b02a57d244163a8db7621860ed91f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:37:57Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-231b02a57d244163a8db7621860ed91f2022-12-21T20:30:32ZengIEEEIEEE Access2169-35362020-01-01817045217046010.1109/ACCESS.2020.30241509195856Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible ManipulatorsBehrouz Kharabian0https://orcid.org/0000-0002-8732-2154Hossein Mirinejad1College of Aeronautics and Engineering, Kent State University, Kent, OH, USACollege of Aeronautics and Engineering, Kent State University, Kent, OH, USAIn this article, a hybrid control approach combining sliding mode and H-infinity is proposed for an uncertain single-link flexible manipulator. The sliding mode controller stabilizes the nonlinear manipulator system, while the H-infinity controller enhances the noise rejection capability of the system by reducing the total system nonlinearity. The proposed hybrid controller is designed with the goal of rejecting external noises, hence providing a higher system performance, compared to a pure sliding mode controller. To avoid unintentional consequences of switching between the sliding mode and H-infinity controller, a fuzzy neural network weighting method is designed providing a smooth synthesis of both controller outputs. The neuro-fuzzy method applies a weighted combination of the two controller outputs to the manipulator system. In addition, a novel fuzzy estimation method is used to characterize the unstructured nonlinear disturbances in manipulator systems. The proposed hybrid control approach along with the fuzzy estimator is capable of providing a versatile means to stabilize flexible manipulator systems while maintaining a precise reference trajectory tracking in presence of unstructured uncertainty and nonlinear dynamics, as demonstrated by simulation results.https://ieeexplore.ieee.org/document/9195856/Flexible manipulatorsliding mode controlH-infinityfuzzy neural networkfuzzy estimator |
| spellingShingle | Behrouz Kharabian Hossein Mirinejad Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators IEEE Access Flexible manipulator sliding mode control H-infinity fuzzy neural network fuzzy estimator |
| title | Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators |
| title_full | Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators |
| title_fullStr | Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators |
| title_full_unstemmed | Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators |
| title_short | Hybrid Sliding Mode/H-Infinity Control Approach for Uncertain Flexible Manipulators |
| title_sort | hybrid sliding mode h infinity control approach for uncertain flexible manipulators |
| topic | Flexible manipulator sliding mode control H-infinity fuzzy neural network fuzzy estimator |
| url | https://ieeexplore.ieee.org/document/9195856/ |
| work_keys_str_mv | AT behrouzkharabian hybridslidingmodehinfinitycontrolapproachforuncertainflexiblemanipulators AT hosseinmirinejad hybridslidingmodehinfinitycontrolapproachforuncertainflexiblemanipulators |