New Riccati Velocity Controller of the Spherical Robot
For the spherical robot, an efficient and precise velocity controller suitable for different terrains is crucial. In this paper, a new Riccati controller with feedforward compensation based on Kalman observer (FKO-Riccati controller) with better control performance and stronger robustness is propose...
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Veröffentlicht in: | Journal of intelligent & robotic systems 2023-07, Vol.108 (3), p.51, Article 51 |
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creator | Wang, You Wang, Yixu Liu, Yifan Guan, Xiaoqing Hu, Tao Zhang, Ziang Hao, Jie Li, Guang |
description | For the spherical robot, an efficient and precise velocity controller suitable for different terrains is crucial. In this paper, a new Riccati controller with feedforward compensation based on Kalman observer (FKO-Riccati controller) with better control performance and stronger robustness is proposed for velocity control of the spherical robot. An accurate dynamic model of the robot is established. Based on the model, a Riccati controller with velocity tracking performance and a Kalman velocity observer are proposed, and the output is feedforward compensated. To verify the effectiveness of the proposed controller, a series of experiments were conducted using a spherical robot named Rotunbot. The simulations and experimental results show that no matter what terrain the robot was in, compared with the traditional PID controller, the FKO-Riccati controller had better control performance and stronger robustness, whether it was going straight or turning. |
doi_str_mv | 10.1007/s10846-023-01871-w |
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In this paper, a new Riccati controller with feedforward compensation based on Kalman observer (FKO-Riccati controller) with better control performance and stronger robustness is proposed for velocity control of the spherical robot. An accurate dynamic model of the robot is established. Based on the model, a Riccati controller with velocity tracking performance and a Kalman velocity observer are proposed, and the output is feedforward compensated. To verify the effectiveness of the proposed controller, a series of experiments were conducted using a spherical robot named Rotunbot. The simulations and experimental results show that no matter what terrain the robot was in, compared with the traditional PID controller, the FKO-Riccati controller had better control performance and stronger robustness, whether it was going straight or turning.</description><identifier>ISSN: 0921-0296</identifier><identifier>EISSN: 1573-0409</identifier><identifier>DOI: 10.1007/s10846-023-01871-w</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Artificial Intelligence ; Control ; Control algorithms ; Controllers ; Design ; Dynamic models ; Electrical Engineering ; Energy consumption ; Engineering ; Experiments ; Feedforward control ; Mechanical Engineering ; Mechatronics ; Motion control ; Pneumatics ; Proportional integral derivative ; Robot control ; Robotics ; Robots ; Robust control ; Robustness ; Short Paper ; Simulation ; Tracking control ; Velocity</subject><ispartof>Journal of intelligent & robotic systems, 2023-07, Vol.108 (3), p.51, Article 51</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2023. 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In this paper, a new Riccati controller with feedforward compensation based on Kalman observer (FKO-Riccati controller) with better control performance and stronger robustness is proposed for velocity control of the spherical robot. An accurate dynamic model of the robot is established. Based on the model, a Riccati controller with velocity tracking performance and a Kalman velocity observer are proposed, and the output is feedforward compensated. To verify the effectiveness of the proposed controller, a series of experiments were conducted using a spherical robot named Rotunbot. 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Wang, Yixu ; Liu, Yifan ; Guan, Xiaoqing ; Hu, Tao ; Zhang, Ziang ; Hao, Jie ; Li, Guang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-834528de7d07c6410c8ffe4df22cc5bf0722438ba7c676424efb242d6ed2a7113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial Intelligence</topic><topic>Control</topic><topic>Control algorithms</topic><topic>Controllers</topic><topic>Design</topic><topic>Dynamic models</topic><topic>Electrical Engineering</topic><topic>Energy consumption</topic><topic>Engineering</topic><topic>Experiments</topic><topic>Feedforward control</topic><topic>Mechanical Engineering</topic><topic>Mechatronics</topic><topic>Motion control</topic><topic>Pneumatics</topic><topic>Proportional integral derivative</topic><topic>Robot control</topic><topic>Robotics</topic><topic>Robots</topic><topic>Robust control</topic><topic>Robustness</topic><topic>Short Paper</topic><topic>Simulation</topic><topic>Tracking control</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, You</creatorcontrib><creatorcontrib>Wang, Yixu</creatorcontrib><creatorcontrib>Liu, Yifan</creatorcontrib><creatorcontrib>Guan, Xiaoqing</creatorcontrib><creatorcontrib>Hu, Tao</creatorcontrib><creatorcontrib>Zhang, Ziang</creatorcontrib><creatorcontrib>Hao, Jie</creatorcontrib><creatorcontrib>Li, Guang</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of intelligent & robotic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, You</au><au>Wang, Yixu</au><au>Liu, Yifan</au><au>Guan, Xiaoqing</au><au>Hu, Tao</au><au>Zhang, Ziang</au><au>Hao, Jie</au><au>Li, Guang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New Riccati Velocity Controller of the Spherical Robot</atitle><jtitle>Journal of intelligent & robotic systems</jtitle><stitle>J Intell Robot Syst</stitle><date>2023-07-01</date><risdate>2023</risdate><volume>108</volume><issue>3</issue><spage>51</spage><pages>51-</pages><artnum>51</artnum><issn>0921-0296</issn><eissn>1573-0409</eissn><abstract>For the spherical robot, an efficient and precise velocity controller suitable for different terrains is crucial. In this paper, a new Riccati controller with feedforward compensation based on Kalman observer (FKO-Riccati controller) with better control performance and stronger robustness is proposed for velocity control of the spherical robot. An accurate dynamic model of the robot is established. Based on the model, a Riccati controller with velocity tracking performance and a Kalman velocity observer are proposed, and the output is feedforward compensated. To verify the effectiveness of the proposed controller, a series of experiments were conducted using a spherical robot named Rotunbot. 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subjects | Artificial Intelligence Control Control algorithms Controllers Design Dynamic models Electrical Engineering Energy consumption Engineering Experiments Feedforward control Mechanical Engineering Mechatronics Motion control Pneumatics Proportional integral derivative Robot control Robotics Robots Robust control Robustness Short Paper Simulation Tracking control Velocity |
title | New Riccati Velocity Controller of the Spherical Robot |
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