Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization
This paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov functi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/22/10096 |
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| author | Ruochen Zhang Hyeung-Sik Choi Dongwook Jung Hyunjoon Cho Phan Huy Nam Anh Mai The Vu |
| author_facet | Ruochen Zhang Hyeung-Sik Choi Dongwook Jung Hyunjoon Cho Phan Huy Nam Anh Mai The Vu |
| author_sort | Ruochen Zhang |
| collection | DOAJ |
| description | This paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov function (BLF) and adaptive neural network strategies, ensures rapid convergence, effective vibration suppression, and the robust handling of system uncertainties and input saturation. The ISSA, inspired by the foraging behavior of sparrows, improves search efficiency through dynamic weight adjustments and chaotic mapping, balancing global and local search capabilities. By optimizing control parameters, ISSA minimizes tracking errors. Simulation results demonstrate that the combined FTC and ISSA approach significantly reduces tracking errors and improves response speed compared to the use of FTC alone, underscoring its potential for achieving high-precision control in robotic arms and offering a promising direction for precise robotic control applications. |
| format | Article |
| id | doaj-art-128ceb1cddce4ca5be7cce96cfee0436 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-128ceb1cddce4ca5be7cce96cfee04362024-11-26T17:47:28ZengMDPI AGApplied Sciences2076-34172024-11-0114221009610.3390/app142210096Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance OptimizationRuochen Zhang0Hyeung-Sik Choi1Dongwook Jung2Hyunjoon Cho3Phan Huy Nam Anh4Mai The Vu5Department of Mechanical Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Mechanical Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Mechanical Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Mechanical Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Mechanical Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Artificial Intelligence and Robotics, Sejong University, Seoul 05006, Republic of KoreaThis paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov function (BLF) and adaptive neural network strategies, ensures rapid convergence, effective vibration suppression, and the robust handling of system uncertainties and input saturation. The ISSA, inspired by the foraging behavior of sparrows, improves search efficiency through dynamic weight adjustments and chaotic mapping, balancing global and local search capabilities. By optimizing control parameters, ISSA minimizes tracking errors. Simulation results demonstrate that the combined FTC and ISSA approach significantly reduces tracking errors and improves response speed compared to the use of FTC alone, underscoring its potential for achieving high-precision control in robotic arms and offering a promising direction for precise robotic control applications.https://www.mdpi.com/2076-3417/14/22/10096fixed-time controlsparrow search algorithmBarrier Lyapunovinput saturationrobotic arm |
| spellingShingle | Ruochen Zhang Hyeung-Sik Choi Dongwook Jung Hyunjoon Cho Phan Huy Nam Anh Mai The Vu Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization Applied Sciences fixed-time control sparrow search algorithm Barrier Lyapunov input saturation robotic arm |
| title | Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization |
| title_full | Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization |
| title_fullStr | Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization |
| title_full_unstemmed | Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization |
| title_short | Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization |
| title_sort | fixed time control with an improved sparrow search algorithm for robotic arm performance optimization |
| topic | fixed-time control sparrow search algorithm Barrier Lyapunov input saturation robotic arm |
| url | https://www.mdpi.com/2076-3417/14/22/10096 |
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