Learning discrete linear systems with the orthogonal learning algorithm |
| |
| Affiliation: | 1. Universidad Simón Bolı́var, Centro de Automatización Industrial, Apartado 89000, Caracas 1080, Venezuela;2. Departamento de Ingenierı́a de Sistemas y Automática, Facultad de Ciencias, Universidad de Valladolid, C/ Prado de la Magdalena S/N, Valladolid 47011, Spain;1. Inception Institute of AI, United Arab Emirates;2. Mohamad bin Zayed University of AI, United Arab Emirates;1. Department of Athletics, National Taiwan University of Science and Technology, 43, Sec.4, Keelung Rd., Taipei 106, Taiwan, ROC;2. Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, 43, Sec.4, Keelung Rd., Taipei 106, Taiwan, ROC;3. Graduate Institute of Science Education, National Taiwan Normal University, 88. Sec. 4, Tingchou Rd., Taipei 116, Taiwan, ROC;1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, PR China;2. The Shandong Province Key Laboratoty of Digital Media Technology, Shandong University of Finance and Economics, Jinan 250014, PR China;3. School of Computer Science and Technology, Shandong University, Jinan 250101, PR China;1. School of Electrical and Information Engineering, Hubei Key Laboratory of Optical Information and Pattern Recognition, Wuhan Institute of Technology;2. LiuFang Campus, No.206, Guanggu 1st road, Donghu New and High Technology Development Zone, Wuhan, Hubei Province, PR China |
| |
| Abstract: | The orthogonal learning algorithm (OLA), based on the linear least-squares error, provides a useful tool to the problem of generating a good discrete model out of a continuous linear system. It is shown in this paper as the learning capabilities of the OLA can be used to determine such an equivalent model along with the generation of the required data. The procedure has been applied to plants of several types like high-order, integrating and non-minimum phase; all of them including an input delay. Discrete PIDs have also been implemented. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
