Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles
For long-term missions in complex seas, the onboard energy resources of autonomous underwater vehicles (AUVs) are limited. Thus, energy consumption reduction is an important aspect of the study of AUVs. This paper addresses energy consumption reduction using model predictive control (MPC) based on t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/19/1/162 |
| _version_ | 1811300201870131200 |
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| author | Feng Yao Chao Yang Mingjun Zhang Yujia Wang |
| author_facet | Feng Yao Chao Yang Mingjun Zhang Yujia Wang |
| author_sort | Feng Yao |
| collection | DOAJ |
| description | For long-term missions in complex seas, the onboard energy resources of autonomous underwater vehicles (AUVs) are limited. Thus, energy consumption reduction is an important aspect of the study of AUVs. This paper addresses energy consumption reduction using model predictive control (MPC) based on the state space model of AUVs for trajectory tracking control. Unlike the previous approaches, which use a cost function that consists of quadratic deviations of the predicted controlled output from the reference trajectory and quadratic input changes, a term of quadratic energy (i.e., quadratic input) is introduced into the cost function in this paper. Then, the MPC control law with the new cost function is constructed, and an analysis on the effect of the quadratic energy term on the stability is given. Finally, simulation results for depth tracking control are given to demonstrate the feasibility and effectiveness of the improved MPC on energy consumption optimization for AUVs. |
| first_indexed | 2024-04-13T06:47:47Z |
| format | Article |
| id | doaj.art-914aa93a7aca4787808e3e3871940ed6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:47:47Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-914aa93a7aca4787808e3e3871940ed62022-12-22T02:57:30ZengMDPI AGSensors1424-82202019-01-0119116210.3390/s19010162s19010162Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater VehiclesFeng Yao0Chao Yang1Mingjun Zhang2Yujia Wang3College of Mechanical and Electrical Engineering, Harbin Engineering University, Nangang District, Harbin 150001, ChinaCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Nangang District, Harbin 150001, ChinaCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Nangang District, Harbin 150001, ChinaCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Nangang District, Harbin 150001, ChinaFor long-term missions in complex seas, the onboard energy resources of autonomous underwater vehicles (AUVs) are limited. Thus, energy consumption reduction is an important aspect of the study of AUVs. This paper addresses energy consumption reduction using model predictive control (MPC) based on the state space model of AUVs for trajectory tracking control. Unlike the previous approaches, which use a cost function that consists of quadratic deviations of the predicted controlled output from the reference trajectory and quadratic input changes, a term of quadratic energy (i.e., quadratic input) is introduced into the cost function in this paper. Then, the MPC control law with the new cost function is constructed, and an analysis on the effect of the quadratic energy term on the stability is given. Finally, simulation results for depth tracking control are given to demonstrate the feasibility and effectiveness of the improved MPC on energy consumption optimization for AUVs.http://www.mdpi.com/1424-8220/19/1/162autonomous underwater vehiclesmodel predictive controltrajectory trackingenergy consumption optimizationcost function |
| spellingShingle | Feng Yao Chao Yang Mingjun Zhang Yujia Wang Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles Sensors autonomous underwater vehicles model predictive control trajectory tracking energy consumption optimization cost function |
| title | Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles |
| title_full | Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles |
| title_fullStr | Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles |
| title_full_unstemmed | Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles |
| title_short | Optimization of the Energy Consumption of Depth Tracking Control Based on Model Predictive Control for Autonomous Underwater Vehicles |
| title_sort | optimization of the energy consumption of depth tracking control based on model predictive control for autonomous underwater vehicles |
| topic | autonomous underwater vehicles model predictive control trajectory tracking energy consumption optimization cost function |
| url | http://www.mdpi.com/1424-8220/19/1/162 |
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