Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique
文献类型：期刊论文
| 作者 | Wen, Guoxing2; Ge, Shuzhi Sam3,4; Chen, C. L. Philip5,6,7; Tu, Fangwen3; Wang, Shengnan1 |
| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 2019-09-01 |
| 卷号 | 49期号:9页码:3420-3431 |
| 关键词 | Actor-critic architecture Lyapunov stability optimized backstepping (OB) reinforcement learning (RL) surface vessel |
| ISSN号 | 2168-2267 |
| DOI | 10.1109/TCYB.2018.2844177 |
| 通讯作者 | Wen, Guoxing(gxwen@live.cn) |
| 英文摘要 | In this paper, a tracking control approach for surface vessel is developed based on the new control technique named optimized backstepping (OB), which considers optimization as a backstepping design principle. Since surface vessel systems are modeled by second-order dynamic in strict feedback form, backstepping is an ideal technique for finishing the tracking task. In the backstepping control of surface vessel, the virtual and actual controls are designed to be the optimized solutions of corresponding subsystems, therefore the overall control is optimized. In general, optimization control is designed based on the solution of Hamilton-Jacobi-Bellman equation. However, solving the equation is very difficult or even impossible due to the inherent nonlinearity and complexity. In order to overcome the difficulty, the reinforcement learning (RL) strategy of actor-critic architecture is usually considered, of which the critic and actor are utilized for evaluating the control performance and executing the control behavior, respectively. By employing the actor-critic RL algorithm for both virtual and actual controls of the vessel, it is proven that the desired optimizing and tracking performances can be arrived. Simulation results further demonstrate effectiveness of the proposed surface vessel control. |
| WOS关键词 | NONLINEAR-SYSTEMS ; ROBUST-CONTROL ; STABILIZATION |
| 资助项目 | Shandong Provincial Natural Science Foundation, China[ZR2018MF015] ; Binzhou University[2016Y14] ; National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61603094] ; National Natural Science Foundation of China[61703050] ; Macau Science and Technology Development Fund[019/2015/A] ; Macau Science and Technology Development Fund[024/2015/AMJ] ; Macau Science and Technology Development Fund[079/2017/A2] ; University Macau MYR Grant |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000470988800017 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Shandong Provincial Natural Science Foundation, China ; Binzhou University ; National Natural Science Foundation of China ; Macau Science and Technology Development Fund ; University Macau MYR Grant |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27848]  |
| 专题 | 离退休人员 |
| 通讯作者 | Wen, Guoxing |
| 作者单位 | 1.Binzhou Univ, Sch Econ & Management, Binzhou 256600, Peoples R China 2.Binzhou Univ, Dept Math, Binzhou 256600, Peoples R China 3.Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore 4.Natl Univ Singapore, Social Robot Lab, Interact Digital Media Inst, Singapore 117576, Singapore 5.Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau 99999, Peoples R China 6.Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China 7.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wen, Guoxing,Ge, Shuzhi Sam,Chen, C. L. Philip,et al. Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique[J]. IEEE TRANSACTIONS ON CYBERNETICS,2019,49(9):3420-3431. |
| APA | Wen, Guoxing,Ge, Shuzhi Sam,Chen, C. L. Philip,Tu, Fangwen,&Wang, Shengnan.(2019).Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique.IEEE TRANSACTIONS ON CYBERNETICS,49(9),3420-3431. |
| MLA | Wen, Guoxing,et al."Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique".IEEE TRANSACTIONS ON CYBERNETICS 49.9(2019):3420-3431. |
入库方式： OAI收割
来源：自动化研究所
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