Fahmizal Fahmizal, Muhammad Arrofiq, Ronald Adrian, Afrizal Mayub
{"title":"Robot Inverted Pendulum Beroda Dua (IPBD) dengan Kendali Linear Quadratic Regulator (LQR)","authors":"Fahmizal Fahmizal, Muhammad Arrofiq, Ronald Adrian, Afrizal Mayub","doi":"10.26760/ELKOMIKA.V7I2.224","DOIUrl":null,"url":null,"abstract":"ABSTRAKMakalah ini memaparkan proses pemodelan robot inverted pendulum beroda dua (IPBD) menggunakan dinamika Lagrange. Setelah sistem model robot IPBD diperoleh, teknik kendali optimal dalam hal ini menggunakan linear quadratic regulator (LQR) digunakan untuk melihat step respon sistem dan tanggapan respon sistem terhadap gangguan. Sebelum kendali LQR diimplementasikan, simulasi menggunakan Simulink Matlab dilakukan untuk mendapat parameter gain K pada kendali LQR. Selanjutnya, dengan mengubah-ubah matriks pembobot Q akan diperoleh variasi gain K. Pada penelitian ini dilakukan variasi matriks pembobotan Q sebanyak lima jenis. Sedangkan matriks elemen R dituning dengan nilai satu. Dari hasil pengujian diperoleh bahwa dengan membesarkan pembobotan matriks Q, dihasilkan respon menuju keadaan steady lebih cepat dan overshoot berkurang. Parameter gain K dari hasil simulasi selanjutnya akan diimplementasikan secara embedded programming ke dalam Arduino Uno pada sistem robot IPBD.Kata kunci: Inverted pendulum beroda, Pemodelan, LQR ABSTRACTThis paper describes the process of modeling two-wheeled pendulum inverted robots (IPBD) using the Lagrange dynamics. After the IPBD robot model system was obtained, the optimal control technique in this case using a linear quadratic regulator (LQR) was used to see the system response step and the response of the system response to interference. Before the LQR control is implemented, simulation using Matlab Simulink is conducted to get the gain K parameter on the LQR control. Furthermore, by varying the weighting matrix Q, the gain variation K will be obtained. There are five types of Q weighting matrix in this research and the R element matric is tuned with a value of 1. From the test, obtained results show that by raising the weighting matrix Q is produced a faster response to the steady state and overshoot is reduced. At the final stage, the gain K parameter from the simulation results will be implemented by embedded programming into Arduino Uno on the IPBD robot system.Keywords: Wheeled inverted pendulum, Modelling, LQR","PeriodicalId":344430,"journal":{"name":"ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26760/ELKOMIKA.V7I2.224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
ABSTRAKMakalah ini memaparkan proses pemodelan robot inverted pendulum beroda dua (IPBD) menggunakan dinamika Lagrange. Setelah sistem model robot IPBD diperoleh, teknik kendali optimal dalam hal ini menggunakan linear quadratic regulator (LQR) digunakan untuk melihat step respon sistem dan tanggapan respon sistem terhadap gangguan. Sebelum kendali LQR diimplementasikan, simulasi menggunakan Simulink Matlab dilakukan untuk mendapat parameter gain K pada kendali LQR. Selanjutnya, dengan mengubah-ubah matriks pembobot Q akan diperoleh variasi gain K. Pada penelitian ini dilakukan variasi matriks pembobotan Q sebanyak lima jenis. Sedangkan matriks elemen R dituning dengan nilai satu. Dari hasil pengujian diperoleh bahwa dengan membesarkan pembobotan matriks Q, dihasilkan respon menuju keadaan steady lebih cepat dan overshoot berkurang. Parameter gain K dari hasil simulasi selanjutnya akan diimplementasikan secara embedded programming ke dalam Arduino Uno pada sistem robot IPBD.Kata kunci: Inverted pendulum beroda, Pemodelan, LQR ABSTRACTThis paper describes the process of modeling two-wheeled pendulum inverted robots (IPBD) using the Lagrange dynamics. After the IPBD robot model system was obtained, the optimal control technique in this case using a linear quadratic regulator (LQR) was used to see the system response step and the response of the system response to interference. Before the LQR control is implemented, simulation using Matlab Simulink is conducted to get the gain K parameter on the LQR control. Furthermore, by varying the weighting matrix Q, the gain variation K will be obtained. There are five types of Q weighting matrix in this research and the R element matric is tuned with a value of 1. From the test, obtained results show that by raising the weighting matrix Q is produced a faster response to the steady state and overshoot is reduced. At the final stage, the gain K parameter from the simulation results will be implemented by embedded programming into Arduino Uno on the IPBD robot system.Keywords: Wheeled inverted pendulum, Modelling, LQR
这篇论文阐述了利用拉格朗热动力学进行双轮机器人逆变摆(IPBD)建模过程。在IPBD模型系统获得后,采用线性quadratic调节器(LQR)用于观察系统反应步骤和系统对干扰的反应反应。在LQR控制被执行之前,使用Matlab模拟进行模拟,以获得LQR控制的增益参数。接下来,通过强化Q音域,将获得增益矩阵的变体。而R元素矩阵的衰减值为1。从测试结果中可以得到的是,通过增加Q矩阵入侵,可以产生对稳定更快和更快的反应。下一个模拟结果的增益参数将被嵌入编程,在IPBD机器人系统上实现。关键字:旋转钟摆变型,模型,LQR abstract这篇论文描述了用“反式机器人”(IPBD)进行模型模型的过程。在IPBD模型系统被拆除后,使用线性四轴调节器(LQR)查看系统响应步骤和系统响应进行干扰。在LQR控制实施之前,使用Matlab Simulink进行模拟,目的是在LQR控制上获得增益K参数。Furthermore, by varying the weghting matrix Q,增益变量将被排除。在这个研究和R元素矩阵中有5个等价物,调校了1的值。从测试中,令人不安的结果显示,通过培育强度矩阵Q,可以更快地对稳定和超速做出反应。在最后阶段,结果模拟的增益参数将通过嵌入程序在IPBD机器人系统上实现。旋转,旋转,LQR