{"title":"Integrated Controller Design for Underactuated Nonlinear System","authors":"A. Abougarair, N. A. Shashoa","doi":"10.1109/ICPC2T53885.2022.9776984","DOIUrl":null,"url":null,"abstract":"The Underactuated systems are exemplified by the Two-Wheeled self-balancing Mobile Robot (TWMR). The system's strong nonlinearity and MIMO make control a fascinating topic. This paper investigates the balancing and tracking control of TWMR using strong integrated controller. The two independently motorized wheels in this mechatronic system track the target reference and investigate a balancing at the gravity center above axis of the wheels' rotation where model fluctuations and an external disruption are included in the consideration. In this work, the innovative controller is presented and tested as a coupling controller based on the aforementioned notions to satisfy considered design objectives. The proposed controller depends on linking several algorithms with each other, where the integrated controller design passes through three phases that are sequential and dependent on each other. In stage one LQR is designed with an IC-based reference control system (LQRIC Based MRCS). Stage two, a dual-loop parallel control of PID-based LQRIC (PCDL-PID) is designed, and in the final stage in this design, The sequential quadratic programming (SQP) is used to set parameters of the final designed control. Evaluation of navigation and balance abilities for TWMR are tested with different scenarios, the designed controller is investigated to observe the behavior of the robot in various targets and its effectiveness is validated. The most significant advantages of designed controllers are that it renders the control system insensitive to external disturbances and model uncertainty.","PeriodicalId":283298,"journal":{"name":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"8 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPC2T53885.2022.9776984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The Underactuated systems are exemplified by the Two-Wheeled self-balancing Mobile Robot (TWMR). The system's strong nonlinearity and MIMO make control a fascinating topic. This paper investigates the balancing and tracking control of TWMR using strong integrated controller. The two independently motorized wheels in this mechatronic system track the target reference and investigate a balancing at the gravity center above axis of the wheels' rotation where model fluctuations and an external disruption are included in the consideration. In this work, the innovative controller is presented and tested as a coupling controller based on the aforementioned notions to satisfy considered design objectives. The proposed controller depends on linking several algorithms with each other, where the integrated controller design passes through three phases that are sequential and dependent on each other. In stage one LQR is designed with an IC-based reference control system (LQRIC Based MRCS). Stage two, a dual-loop parallel control of PID-based LQRIC (PCDL-PID) is designed, and in the final stage in this design, The sequential quadratic programming (SQP) is used to set parameters of the final designed control. Evaluation of navigation and balance abilities for TWMR are tested with different scenarios, the designed controller is investigated to observe the behavior of the robot in various targets and its effectiveness is validated. The most significant advantages of designed controllers are that it renders the control system insensitive to external disturbances and model uncertainty.