{"title":"欠驱动起重机的高效轨迹规划与跟踪控制","authors":"Xinyu Long, Mingwei Sun, Zengqiang Chen","doi":"10.61416/ceai.v25i2.8307","DOIUrl":null,"url":null,"abstract":"The crane is a typical underactuated plant, which makes the trajectory planning and control to be challenging. To solve this problem, parameterized reduced-dimension trajectory planning and tracking control are carried out. The plant is reduced in dimension by using the differential flatness (DF) method, wherein the state and control variables are represented directly through the flat output (FO). Combined with the pseudospectral method (PSM) wherein multiple constraints are taken into account, the FO is parameterized by using the polynomial functions, and the trajectory planning in the FO space is transformed into a parameter planning problem. By doing so, it can reduce the degree of freedoms to be optimized. For the high-order terms and various disturbances in the FO, the extended state observer is used for estimation and compensation. Both numerical simulation and hardware experiments are performed to demonstrate the feasibility and efficiency of the proposed method. DOI: 10.61416/ceai.v25i2.8307","PeriodicalId":50616,"journal":{"name":"Control Engineering and Applied Informatics","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient Trajectory Planning and Tracking Control for Underactuated Crane\",\"authors\":\"Xinyu Long, Mingwei Sun, Zengqiang Chen\",\"doi\":\"10.61416/ceai.v25i2.8307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The crane is a typical underactuated plant, which makes the trajectory planning and control to be challenging. To solve this problem, parameterized reduced-dimension trajectory planning and tracking control are carried out. The plant is reduced in dimension by using the differential flatness (DF) method, wherein the state and control variables are represented directly through the flat output (FO). Combined with the pseudospectral method (PSM) wherein multiple constraints are taken into account, the FO is parameterized by using the polynomial functions, and the trajectory planning in the FO space is transformed into a parameter planning problem. By doing so, it can reduce the degree of freedoms to be optimized. For the high-order terms and various disturbances in the FO, the extended state observer is used for estimation and compensation. Both numerical simulation and hardware experiments are performed to demonstrate the feasibility and efficiency of the proposed method. DOI: 10.61416/ceai.v25i2.8307\",\"PeriodicalId\":50616,\"journal\":{\"name\":\"Control Engineering and Applied Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2023-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Control Engineering and Applied Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.61416/ceai.v25i2.8307\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering and Applied Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.61416/ceai.v25i2.8307","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Efficient Trajectory Planning and Tracking Control for Underactuated Crane
The crane is a typical underactuated plant, which makes the trajectory planning and control to be challenging. To solve this problem, parameterized reduced-dimension trajectory planning and tracking control are carried out. The plant is reduced in dimension by using the differential flatness (DF) method, wherein the state and control variables are represented directly through the flat output (FO). Combined with the pseudospectral method (PSM) wherein multiple constraints are taken into account, the FO is parameterized by using the polynomial functions, and the trajectory planning in the FO space is transformed into a parameter planning problem. By doing so, it can reduce the degree of freedoms to be optimized. For the high-order terms and various disturbances in the FO, the extended state observer is used for estimation and compensation. Both numerical simulation and hardware experiments are performed to demonstrate the feasibility and efficiency of the proposed method. DOI: 10.61416/ceai.v25i2.8307
期刊介绍:
The Journal is promoting theoretical and practical results in a large research field of Control Engineering and Technical Informatics. It has been published since 1999 under the Romanian Society of Control Engineering and Technical Informatics coordination, in its quality of IFAC Romanian National Member Organization and it appears quarterly.
Each issue has up to 12 papers from various areas such as control theory, computer engineering, and applied informatics. Basic topics included in our Journal since 1999 have been time-invariant control systems, including robustness, stability, time delay aspects; advanced control strategies, including adaptive, predictive, nonlinear, intelligent, multi-model techniques; intelligent control techniques such as fuzzy, neural, genetic algorithms, and expert systems; and discrete event and hybrid systems, networks and embedded systems. Application areas covered have been environmental engineering, power systems, biomedical engineering, industrial and mobile robotics, and manufacturing.