Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control
Aiming at the high-precision trajectory tracking problem of the new surface and underwater joint observation system (SUJOS) in the ocean remote sensing monitoring mission under complex sea conditions, especially at the problem of excessive tracking errors and slow convergence of actual trajectory os...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/5/925 |
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| author | Qichao Wu Yunli Nie Shengli Wang Shihao Zhang Tianze Wang Yizhe Huang |
| author_facet | Qichao Wu Yunli Nie Shengli Wang Shihao Zhang Tianze Wang Yizhe Huang |
| author_sort | Qichao Wu |
| collection | DOAJ |
| description | Aiming at the high-precision trajectory tracking problem of the new surface and underwater joint observation system (SUJOS) in the ocean remote sensing monitoring mission under complex sea conditions, especially at the problem of excessive tracking errors and slow convergence of actual trajectory oscillations caused by the wide range of angular changes in the motion trajectory, a real-time optimization improved model predictive control (IMPC) trajectory tracking method based on fuzzy control is proposed. Initially, the novel observation platform has been designed, and its mathematical model has been systematically established. In addition, this study optimizes the MPC trajectory tracking framework by integrating the least squares adaptive algorithm and the Extended Alternating Direction Method of Multipliers (EADMM). In addition, a fuzzy controller, optimized using a genetic algorithm, an output of real-time optimization coefficients, is employed to dynamically adjust and optimize the bias matrix within the objective function of the IMPC. Consequently, the real-time performance and accuracy of the system’s trajectory tracking are significantly enhanced. Ultimately, through comprehensive simulation and practical experimental verification, it is demonstrated that the real-time optimization IMPC algorithm exhibits commendable real-time and optimization performance, which markedly enhances the accuracy for trajectory tracking, and further validates the stability of the controller. |
| format | Article |
| id | doaj-art-8e9128c1c9cb400b940028fa45b2bfca |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-8e9128c1c9cb400b940028fa45b2bfca2025-08-20T02:59:07ZengMDPI AGRemote Sensing2072-42922025-03-0117592510.3390/rs17050925Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy ControlQichao Wu0Yunli Nie1Shengli Wang2Shihao Zhang3Tianze Wang4Yizhe Huang5College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaAiming at the high-precision trajectory tracking problem of the new surface and underwater joint observation system (SUJOS) in the ocean remote sensing monitoring mission under complex sea conditions, especially at the problem of excessive tracking errors and slow convergence of actual trajectory oscillations caused by the wide range of angular changes in the motion trajectory, a real-time optimization improved model predictive control (IMPC) trajectory tracking method based on fuzzy control is proposed. Initially, the novel observation platform has been designed, and its mathematical model has been systematically established. In addition, this study optimizes the MPC trajectory tracking framework by integrating the least squares adaptive algorithm and the Extended Alternating Direction Method of Multipliers (EADMM). In addition, a fuzzy controller, optimized using a genetic algorithm, an output of real-time optimization coefficients, is employed to dynamically adjust and optimize the bias matrix within the objective function of the IMPC. Consequently, the real-time performance and accuracy of the system’s trajectory tracking are significantly enhanced. Ultimately, through comprehensive simulation and practical experimental verification, it is demonstrated that the real-time optimization IMPC algorithm exhibits commendable real-time and optimization performance, which markedly enhances the accuracy for trajectory tracking, and further validates the stability of the controller.https://www.mdpi.com/2072-4292/17/5/925remote sensing monitoringtrajectory trackingIMPCfuzzy controlgenetic algorithmreal-time optimization |
| spellingShingle | Qichao Wu Yunli Nie Shengli Wang Shihao Zhang Tianze Wang Yizhe Huang Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control Remote Sensing remote sensing monitoring trajectory tracking IMPC fuzzy control genetic algorithm real-time optimization |
| title | Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control |
| title_full | Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control |
| title_fullStr | Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control |
| title_full_unstemmed | Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control |
| title_short | Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control |
| title_sort | real time optimization improved model predictive control trajectory tracking for a surface and underwater joint observation system based on genetic algorithm fuzzy control |
| topic | remote sensing monitoring trajectory tracking IMPC fuzzy control genetic algorithm real-time optimization |
| url | https://www.mdpi.com/2072-4292/17/5/925 |
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