Wavenet fuzzy PID controller for nonlinear MIMO systems: Experimental validation on a high-end haptic robotic interface |
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| Affiliation: | 1. Centro de Investigación en Tecnologías de Información y Sistemas, Universidad Autónoma del Estado de Hidalgo, Mineral de la Reforma, Carr. Pachuca-Tulancigo, Km. 4.5, Hidalgo, Mexico;2. Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV-Unidad Saltillo), Carr. Saltillo-Monterrey, Km. 13.5, Ramos Arizpe Coah., Mexico;1. Federal University of Technology (UTFPR), Elect. Eng. Dept., Av. Alberto Carazzai, 1640, 86300-000 Cornélio Procópio, PR, Brazil;2. Federal University of São Carlos (UFSCAR), Rodovia Washington Luís, km 235 – SP 310, 13565-905 São Carlos, SP, Brazil;1. School of Software Engineering, Chongqing University, Chongqing 400044, PR China;2. School of Computing, National University of Singapore, Singapore 117417, Singapore;3. School of Information Science and Engineering, Lanzhou University, Gansu 730000, PR China;4. Faculty of Computer and Information Science, Southwest University, Chongqing 400715, PR China;5. Faculty of Engineering, The University of Sydney, Sydney 2006, Australia;1. School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China;2. School of Electronic Information, Wuhan University, Wuhan 430072, China;1. Land Forces Academy, 3-5 Revolutiei St., 550170 Sibiu, Romania;2. Technical University of Munich, 80333 Munich, Germany;1. School of Computer and Software Engineering, Xihua University, Chengdu 610039, China;2. School of Digital Media, Jiangnan University, Wuxi 214122, China |
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| Abstract: | A novel global PID control scheme for nonlinear MIMO systems is proposed and implemented for a robot as study case, this scheme is called AWFPID from its adaptive wavelet fuzzy PID control structure. Basically, it identifies inverse error dynamics using a radial basis neural network with daughter RASP1 wavelets activation function; its output is in cascaded with an infinite impulse response (IIR) filter to prune irrelevant signals and nodes as well as to recover a canonical form. Then, online adaptive fuzzy tuning of a discrete PID regulator is proposed, whose closed-loop guarantees global regulation for nonlinear dynamical plants. The wavelet network includes a fuzzy inference system for online tuning of learning rates. A real-time experimental study on a three degrees of freedom haptic interface, the PHANToM Premium 1.0A, highlights the regulation with smooth control effort without using the mathematical model of the robot. |
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| Keywords: | Identification Wavelet fuzzy neural network Self-adaptive algorithms PHANToM robot |
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