The inverted pendulum problem is one of the most important problems in control theory and has been studied excessively in control literatures. When control systems have strong requirements, the adjustment of the controller is a complex problem. The nonlinear model is useful for control design. In the present work, Volterra polynomial basis function (VPBF) networks have been used to identify a single inverted pendulum on a moving cart (SIPC) system. The inverted pendulum is a benchmark problem of nonlinear multivariable systems with inherent instability. The multivariable system has been considered with a force produced by a DC motor as the input, and four states variables as the outputs. A Fuzzy Logic controller has been used to stabilize the system for closed-loop identification. Here, the nonlinear model of the inverted pendulum has been implemented. The offline structure selection through orthogonal least square algorithm is used for the nonlinear system identification via the basis function selection of Volterra polynomial networks. The neural network is trained using the error between the model's outputs and the plant's actual outputs. The results show good match between predicted and actual outputs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.