Adaptive Fuzzy Control of the Inverted Pendulum Problem

El-Hawwary, Mohamed I.; El-Shafei, A.; Emara, Hassan M.; Fattah, Hossam

doi:10.1109/tcst.2006.880217

Cited by 94 publications

(51 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…18 stabilizes a quadruple inverted pendulum using a variable universe fuzzy controller. The tracking control is achieved in 19 . Systems such as the two-wheel inverted pendulum 20 or the dual axis pendulums 21 have been studied from this perspective.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Control of a chain pendulum: A fuzzy logic approach

Aranda-Escolástico¹,

Guinaldo²,

Santos³

et al. 2016

IJCIS

View full text Add to dashboard Cite

In this paper we present a real application of computational intelligence. Fuzzy control of a non-linear rotary chain pendulum is proposed and implemented on real prototypes. The final aim is to obtain a larger region of attraction for the stabilization of this complex system, that is, a more robust controller. As it is well-known, fuzzy logic exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost when dealing with complex systems. In this case, the control strategy is based on a Takagi-Sugeno fuzzy model of the strongly non-linear multivariable system. Simulation and experimental results on the real plant have been obtained and tested in a rotary inverted pendulum and in a double rotary inverted pendulum. They have been compared to other feedback control strategies such as Full State Feedback or Linear Quadratic Regulator with encouraging results. Fuzzy control allows to enlarge the stability region of control. Indeed, the region of attraction and therefore the stabilization has been enlarged up to over 17% for the real system.

show abstract

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Control of a chain pendulum: A fuzzy logic approach

Aranda-Escolástico¹,

Guinaldo²,

Santos³

et al. 2016

IJCIS

View full text Add to dashboard Cite

show abstract

“…The inverted pendulum system is one of the classical examples used in many experiments dealing with classical as well as modern control, and it is often used to test the effectiveness of different controlling schemes [13][14][15][16]. So in this chapter, to examine the effectiveness of the proposed TDRNN model, we investigate the application of the TDRNN to the control of inverted pendulums.…”

Section: Inverted Pendulum Controlmentioning

confidence: 99%

Recurrent Neural Network-Based Adaptive Controller Design For Nonlinear Dynamical Systems

Ge¹,

Tan²

2012

Recurrent Neural Networks and Soft Computing

View full text Add to dashboard Cite

“…In the past several years, there are many literatures to study the inverted pendulum (Tao et al 2008;Takimoto et al 2008;Casavola et al 2004Casavola et al , 2006Lin and Mon 2005;El-Hawwary et al 2006;Er et al 2002). The main topic of this research is how to keep the pendulum balance at the upright position.…”

Section: Introductionmentioning

confidence: 97%

Robust intelligent backstepping tracking control for wheeled inverted pendulum

2011

View full text Add to dashboard Cite

In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation controller (AORCMAC) and H ? control technique is proposed for wheeled inverted pendulums (WIPs) with unknown system dynamics and external disturbance. The AORCMAC is a nonlinear adaptive system with simple computation, good generalization capability and fast learning property. Therefore, the WIP can stand upright when it moves to a designed position stably. In the proposed control system, an AORCMAC is used to copy an ideal backstepping control, and a robust H ? controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the RIBTC system are derived based on the Lyapunov stability analysis, the Taylor linearization technique and H ? control theory, so that the stability of the closed-loop system and H ? tracking performance can be guaranteed. The proposed control scheme is practical and efficacious for WIPs by simulation results.

show abstract

Adaptive Fuzzy Control of the Inverted Pendulum Problem

Cited by 94 publications

References 16 publications

Control of a chain pendulum: A fuzzy logic approach

Control of a chain pendulum: A fuzzy logic approach

Recurrent Neural Network-Based Adaptive Controller Design For Nonlinear Dynamical Systems

Robust intelligent backstepping tracking control for wheeled inverted pendulum

Contact Info

Product

Resources

About