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...

Full description

Saved in:
Bibliographic Details
Main Authors: Qichao Wu, Yunli Nie, Shengli Wang, Shihao Zhang, Tianze Wang, Yizhe Huang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/5/925
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850030807875321856
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
work_keys_str_mv AT qichaowu realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol
AT yunlinie realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol
AT shengliwang realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol
AT shihaozhang realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol
AT tianzewang realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol
AT yizhehuang realtimeoptimizationimprovedmodelpredictivecontroltrajectorytrackingforasurfaceandunderwaterjointobservationsystembasedongeneticalgorithmfuzzycontrol