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FI 2016

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© Thomson Reuters, Journal Citation Reports, 2016

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  • Factor de Impacto: 0,500(2016)
  • 5-años Factor de Impacto: 0,344
  • SCImago Journal Rank (SJR):0,212
  • Source Normalized Impact per Paper (SNIP):0,308

© Thomson Reuters, Journal Citation Reports, 2016

Revista Iberoamericana de Automática e Informática industrial 2017;14:133-40 - DOI: 10.1016/j.riai.2016.12.001
Diseño de un Controlador Difuso mediante la Síntesis Difusa de Lyapunov para la Estabilización de un Péndulo de Rueda Inercial
Design of a fuzzy controller via fuzzy Lyapunov synthesis for the stabilization of an inertial wheel pendulum
Nohe R. Cazarez-Castroa,, , Luis T. Aguilarb, , Selene L. Cardenas-Maciela, , Carlos A. Goribar-Jimeneza, , Mauricio Odreman-Veraa,
a Tecnológico Nacional de México - Instituto Tecnológico de Tijuana, Av. ITR Tijuana y Blvd. Alberto Limón Padilla, S/N, 22510, Tijuana, Baja California, México
b Instituto Politécnico Nacional–CITEDI, avenida Instituto Politécnico Nacional No. 1310 Colonia Nueva Tijuana, Tijuana 22435 México
Resumen

En el presente trabajo se reporta el diseño de un controlador difuso tipo Mamdani para el problema de estabilización de un péndulo de rueda inercial. Las reglas difusas son obtenidas mediante la síntesis difusa de Lyapunov, lo cual permite mantener al mínimo el uso de la heurística, y desde la etapa de diseño garantizar estabilidad en lazo cerrado. Por otra parte el diseño de las reglas difusas es mucho más simple que la ardua tarea de resolver las ecuaciones diferenciales no lineales usadas tradicionalmente para modelar sistemas de control. Merece énfasis especial el hecho de que el diseño se hace libre del modelo matemático del sistema a controlar.

Abstract

In this paper was presented the design of a Mamdani type fuzzy controller to solve the stabilization problem for an inertial wheel pendulum. The fuzzy rule base are designed following the fuzzy Lyapunov synthesis, which guarantee the local asymptotic stability of the closed-loop system, by using a Lyapunov function whose time-derivative is negative semidefinite, while the use of heuristics is minimized in the design process. Moreover, the design of the fuzzy rule base is simplest than the hard task of solve the nonlinear differential equations traditionally used to model control systems. Deserves special emphasis the fact that the design is made without a mathematical model of the inertia wheel pendulum.

Palabras clave
Control difuso, Estabilidad de Lyapunov, Sistema subactuado
Keywords
Fuzzy control, Lyapunov stability, Underactuated system
Referencias
Andary et al., 2009
S. Andary,A. Chemori,S. Krut
Control of the underactuated inertia wheel inverted pendulum for stable limit cycle generation
Advanced Robotics, 23 (2009), pp. 1999-2014
Andrievsky, 2011
B. Andrievsky
Global stabilization of the unstable reaction-wheel pendulum
Automation and Remote Control, 72 (2011), pp. 1981-1993
Becerikli and Celik, 2007
Y. Becerikli,B.K. Celik
Fuzzy control of inverted pendulum and concept of stability using java application
Mathematical and Computer Modelling, 46 (2007), pp. 24-37
Brockett, 1983
R. Brockett
Differential Geometric Control Theory
Ch. Asymptotic stability and feedback stabilization, Birkhäuser, (1983)pp. 181-191
Castillo et al., 2008
O. Castillo,L. Aguilar,N. Cazarez,S. Cardenas
Systematic design of a stable type-2 fuzzy logic controller
Applied Soft Computing, 8 (2008), pp. 1274-1279
Castillo et al., 2006
O. Castillo,N. Cazarez,L. Aguilar,D. Rico
Intelligent control of dynamic systems using type-2 fuzzy logic and stability issues
International Mathematical Forum, 1 (2006), pp. 1371-1382
Cazarez-Castro et al., 2010
N.R. Cazarez-Castro,L.T. Aguilar,O. Castillo
Fuzzy logic control with genetic membership function parameters optimization for the output regulation of a servomechanism with nonlinear backlash
Expert Systems with Applications, 37 (2010), pp. 4368-4378
Hernández, 2003
V.M. Hernández
A combined sliding mode-generalized pi control scheme for swinging up and balancing the inertia wheel pendulum
Asian Journal of Control, 5 (2003), pp. 620-625
Iriarte et al., 2013
R. Iriarte,L.T. Aguilar,L. Fridman
Second order sliding mode tracking controller for inertia wheel pendulum
Journal of the Franklin Institute, 350 (2013), pp. 92-106
Kelly et al., 2000
R. Kelly,J. Llamas,R. Campa
A measurement procedure for viscous and coulomb friction
Instrumentation and Measurement, IEEE Transactions on, 49 (Aug 2000), pp. 857-861
Khalil, 2002
H.K. Khalil
Nonlinear Systems
3rd Edition, Prentice Hall, (2002)
Korotnikov, 1998
V. Korotnikov
Partial Stability and Control
1st Edition., Springer- Birkhäuser Basel, (1998)
Lyapunov, 1892
A. Lyapunov
The general problem of the stability of motion (in russian)
Phd, Univ, (1892)
Mamdani and Assilian, 1975
E. Mamdani,S. Assilian
An experiment in linguistic synthesis with a fuzzy logic controller
International Journal of Man-Machine Studies, 7 (1975), pp. 1-13
Margaliot and Langholz, 1999
M. Margaliot,G. Langholz
Fuzzy lyapunov-based approach to the design of fuzzy controllers
Fuzzy Sets and Systems, 106 (1999), pp. 49-59
Martinez-Soto et al., 2012
R. Martinez-Soto,A. Rodriguez,O. Castillo,L.T. Aguilar
Gain optimization for inertia wheel pendulum stabilization using particle swarm optimization and genetic algorithms
International Journal of Innovative Computing, Information and Control, 8 (2012), pp. 4421-4430
Ng et al., 2013
W.M. Ng,D.E. Chang,S.-H. Song
Four representative applications of the energy shaping method for controlled lagrangian systems
Journal of Electrical Engineering and Technology, 8 (2013), pp. 1579-1589
Qaiser et al., 2006
Qaiser, N., Iqbal, N., Hussain, A., Qaiser, N., 2006. Stabilization of non-linear inertia wheel pendulum system using a new dynamic surface control based technique. In: Engineering of Intelligent Systems, 2006 IEEE International Conference on. pp. 1–6.
Qaiser et al., 2007
N. Qaiser,N. Iqbal,A. Hussain,N. Qaiser
Exponential stabilization of the inertia wheel pendulum using dynamic surface control
Journal of Circuits, Systems and Computers, 16 (2007), pp. 81-92
Ye et al., 2007
H. Ye,H. Wang,H. Wang
Stabilization of a pvtol aircraft and an inertia wheel pendulum using saturation technique
IEEE Transactions on Control Systems Technology, 15 (Nov 2007), pp. 1143-1150
Yi and Yubazaki, 2000
J. Yi,N. Yubazaki
Stabilization fuzzy control of inverted pendulum systems
Artificial Intelligence in Engineering, 14 (2000), pp. 153-163
Autor para correspondencia. (Nohe R. Cazarez-Castro nohe@ieee.org)
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