Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm
When a cross-domain robot (CDR) flies on the water surface, the large pitch angle and roll angle may lead to water flooding into the robot cabin or even overturning. In addition, the CDR is influenced by some uncertain parameters and external disturbances, such as the water resistance and current. T...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/9/7/332 |
| _version_ | 1797441560354226176 |
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| author | Ke Wang Yong Liu Chengwei Huang Wei Bao |
| author_facet | Ke Wang Yong Liu Chengwei Huang Wei Bao |
| author_sort | Ke Wang |
| collection | DOAJ |
| description | When a cross-domain robot (CDR) flies on the water surface, the large pitch angle and roll angle may lead to water flooding into the robot cabin or even overturning. In addition, the CDR is influenced by some uncertain parameters and external disturbances, such as the water resistance and current. To constrain the robot attitude angle and improve the robustness of the controller, a non-singular terminal sliding mode asymmetric barrier control (NTSMABC) algorithm is proposed. All the uncertain disturbances are regarded as a lump disturbance, and a radial basis function neural network (RBFNN) is designed to compensate for the output of the controllers. Unlike the traditional quadrotors, the robot controls the yaw angle by paddles when the robot flies on the water surface. To prevent the actuator saturation and the robot from rolling over due to excessive yaw angular velocity, an adaptive integral sliding mode barrier control (AISMBC) algorithm is proposed to constrain the yaw angular velocity directly. This algorithm adaptively adjusts the gain of the sliding surface to suppress the influence of the lump disturbance on the robot. Another RBFNN is designed to compensate for the output of the controller. Simulation results demonstrate the effectiveness of the proposed control methods. |
| first_indexed | 2024-03-09T12:24:56Z |
| format | Article |
| id | doaj.art-8df873d478254923bf3a3cb290b0cc4a |
| institution | Directory Open Access Journal |
| issn | 2226-4310 |
| language | English |
| last_indexed | 2024-03-09T12:24:56Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj.art-8df873d478254923bf3a3cb290b0cc4a2023-11-30T22:36:09ZengMDPI AGAerospace2226-43102022-06-019733210.3390/aerospace9070332Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control AlgorithmKe Wang0Yong Liu1Chengwei Huang2Wei Bao3School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210018, ChinaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210018, ChinaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210018, ChinaSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210018, ChinaWhen a cross-domain robot (CDR) flies on the water surface, the large pitch angle and roll angle may lead to water flooding into the robot cabin or even overturning. In addition, the CDR is influenced by some uncertain parameters and external disturbances, such as the water resistance and current. To constrain the robot attitude angle and improve the robustness of the controller, a non-singular terminal sliding mode asymmetric barrier control (NTSMABC) algorithm is proposed. All the uncertain disturbances are regarded as a lump disturbance, and a radial basis function neural network (RBFNN) is designed to compensate for the output of the controllers. Unlike the traditional quadrotors, the robot controls the yaw angle by paddles when the robot flies on the water surface. To prevent the actuator saturation and the robot from rolling over due to excessive yaw angular velocity, an adaptive integral sliding mode barrier control (AISMBC) algorithm is proposed to constrain the yaw angular velocity directly. This algorithm adaptively adjusts the gain of the sliding surface to suppress the influence of the lump disturbance on the robot. Another RBFNN is designed to compensate for the output of the controller. Simulation results demonstrate the effectiveness of the proposed control methods.https://www.mdpi.com/2226-4310/9/7/332cross-domain robot (CDR)radial basis function neural network (RBFNN)non-singular terminal sliding mode asymmetric barrier control (NTSMABC)adaptive integral sliding mode barrier control (AISMBC) |
| spellingShingle | Ke Wang Yong Liu Chengwei Huang Wei Bao Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm Aerospace cross-domain robot (CDR) radial basis function neural network (RBFNN) non-singular terminal sliding mode asymmetric barrier control (NTSMABC) adaptive integral sliding mode barrier control (AISMBC) |
| title | Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm |
| title_full | Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm |
| title_fullStr | Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm |
| title_full_unstemmed | Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm |
| title_short | Water Surface Flight Control of a Cross Domain Robot Based on an Adaptive and Robust Sliding Mode Barrier Control Algorithm |
| title_sort | water surface flight control of a cross domain robot based on an adaptive and robust sliding mode barrier control algorithm |
| topic | cross-domain robot (CDR) radial basis function neural network (RBFNN) non-singular terminal sliding mode asymmetric barrier control (NTSMABC) adaptive integral sliding mode barrier control (AISMBC) |
| url | https://www.mdpi.com/2226-4310/9/7/332 |
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