Modeling and Construction of a Furuta Pendulum Prototype

Antonio-Cruz, Mayra; Silva‐Ortigoza, Ramón; Merlo-Zapata, Carlos Alejandro; Villarreal-Cervantes, Miguel Gabriel; Muñoz-Carrillo, D.; Hernández-Guzmán, Victor Manuel

doi:10.1109/icmeae.2014.23

Cited by 9 publications

(3 citation statements)

References 16 publications

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“…The authors of [1] and [7] proposed a linearized model based on a small angle assumption. Others neglected one or more of the cross coupling terms relating the two rotations [1], [3], [6], [8], [9]. The authors of [7] showed, through simulations, that the aforementioned assumption is not acceptable and it could have an important effect on the dynamic response.…”

Section: Introductionmentioning

confidence: 99%

Identifying Friction in a Nonlinear Chaotic System Using a Universal Adaptive Stabilizer

2022

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This paper proposes a friction model parameter identification routine that can work with highly nonlinear and chaotic systems. The chosen system for this study is a passively-actuated tilted Furuta pendulum, which is known to have a highly nonlinear and coupled model. The pendulum is tilted to ensure the existence of a stable equilibrium configuration for all its degrees of freedom, and the link weights are the only external forces applied to the system. A nonlinear analytical model of the pendulum is derived, and a continuous friction model considering static friction, dynamic friction, viscous friction, and the stribeck effect is selected from the literature. A high-gain Universal Adaptive Stabilizer (UAS) observer is designed to identify friction model parameters using joint angle measurements. The methodology is tested in simulation and validated on an experimental setup. Despite the high nonlinearity of the system, the methodology is proven to converge to the exact parameter values, in simulation, and to yield qualitative parameter magnitudes in experiments where the goodness of fit was around 85% on average. The discrepancy between the simulation and the experimental results is attributed to the limitations of the friction model. The main advantage of the proposed method is the significant reduction in computational needs and the time required relative to conventional optimization-based identification routines. The proposed approach yielded more than 99% reduction in the estimation time while being considerably more accurate than the optimization approach in every test performed. One more advantage is that the approach can be easily adapted to fit other models to experimental data.

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Section: Introductionmentioning

confidence: 99%

Identifying Friction in a Nonlinear Chaotic System Using a Universal Adaptive Stabilizer

2022

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“…It is a challenging problem in the area of control engineering applications in linear and nonlinear control, also can be called ''Furuta Pendulum'' [3]. Furuta Pendulum is a simple structure that consists of a high torque servo motor which rotates in the horizontal plane where the pendulums are attached to the horizontal arm which is free to rotate in the vertical plane [4]. The Furuta pendulum system was developed by K. Furuta at Tokyo Institute of Technology and was called the ''TITECH pendulum'' [5].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of the Joint Neuro-Fuzzy Friction Models for a Triple Link Rotary Inverted Pendulum

2020

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In this paper, Neuro-Fuzzy Friction Estimation Models (NFFEM) are developed to estimate the joint friction coefficients in a Triple Link Rotary Inverted Pendulum (TLRIP) system and compared with an Adaptive Friction Estimation Models (AFEM). The different versions of AFEMs and NFFEMs are generated based on each of the following friction estimation models: Non-Conservative Friction Model (NCFM), Linear Friction Model (LFM), and Non-Linear Friction Model (NLFM). The aim of this study is to obtain joint friction models which depend on both velocity and acceleration in a large range of motion trajectory that involves difficult and sudden large changes. In the proposed NFFEMs, joint velocities and accelerations of the TLRIP are used as the input variables of the Neuro-Fuzzy system trained by using a Radial Basis Function Artificial Neural Network (RBANN). Several experiments are conducted on TLRIP system to verify the NFFEMs. In order to determine the estimation performance of the friction models, total Root Mean Squared Errors (RMSE) between position simulation results obtained from each joint friction model and encoders in the experimental setup are computed. Based on the position RMSEs, the NFFEMs produces much better estimation results than the AFEMs. Among NFFEMs, the neuro-fuzzy nonlinear friction model (NFNLM) gives the best results. INDEX TERMS Triple link rotary inverted pendulum (TLRIP), neuro-fuzzy friction estimation and modelling.

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“…Also, in order to validate such a procedure, results from numerical simulations of the system dynamic model were compared with experimental results from the system built. On the other hand, two works were introduced recently by Antonio-Cruz et al [14], [15]. The first one refers to the modeling and construction of a Furuta pendulum prototype, and the second one is associated with the modeling, computer aided design, and construction of a testbed of the aforementioned system.…”

Section: Introductionmentioning

confidence: 99%

Modeling, simulation, and construction of a furuta pendulum test-bed

Antonio-Cruz

Silva‐Ortigoza

Sandoval-Gutierrez

et al. 2015

2015 International Conference on Electronics, Communications and Computers (CONIELECOMP)

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This paper presents a Furuta pendulum as a testbed to experimentally validate automatic control strategies or theoretical concepts associated with nonlinear systems. Herein, the modeling, simulation, and construction of a Furuta pendulum test-bed are introduced step-by-step. The development of the Furuta pendulum mathematical model is achieved by using Lagrange equations of motion. In contrast with other works, the development of this model includes an analysis of the system kinematics. Also, a numerical simulation of the mathematical model is performed via Matlab-Simulink. Furthermore, with the purpose of presenting a different tool for the modeling and simulation of dynamic systems, a graphical model and a graphical simulation of the Furuta pendulum are carried out by means of Working Model 3D. Moreover, a computer aided design of the system under study is accomplished through SolidWorks, based on such a design a test-bed is built. With the intention of verifying that the test-bed built behaves according to the models (numerical one and graphical one) presented herein, experiments with the test-bed in open-loop are carried out by using Matlab-Simulink, ControlDesk, and a DS1104 board from dSPACE.978-1-4799-7436-8/15/$31.00 ©2015 IEEE 978-1-4799-7436-8/15/$31.00 ©2015 IEEE

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Modeling and Construction of a Furuta Pendulum Prototype

Cited by 9 publications

References 16 publications

Identifying Friction in a Nonlinear Chaotic System Using a Universal Adaptive Stabilizer

Identifying Friction in a Nonlinear Chaotic System Using a Universal Adaptive Stabilizer

A Comparative Study of the Joint Neuro-Fuzzy Friction Models for a Triple Link Rotary Inverted Pendulum

Modeling, simulation, and construction of a furuta pendulum test-bed

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