Robust Hybrid Complex Motion Control Using Fuzzy Logic, Inverse Dynamic and PID-Q Controllers
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A simple prototypical hybrid dynamic system, namely the bouncing ball system, is used to illustrate modeling and control of a hybrid dynamic system. This standard system is extended to include a complex inelastic bounce surface and actuation. A nonlinear one-axis prismatic actuator applies a bounce force to the ball to regulate the bounce height. Several controllers are compared with each other in simulations; linear and nonlinear PID, inverse dynamic, and fuzzy logic. Robustness against unmodeled dynamics, parameter variations and external disturbances are shown. SimMechanics is used to model the bounce actuator, bouncing ball system and surface. Simulation results show that the fuzzy logic controller fairs better on average on a complex surface.
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R. Goebel, R. Sanfelice, A. Teel, Hybrid Dynamical Systems, Control Systems, IEEE 29.2 (2009) 28-93.
A. J. van der Schaft, J. M. Schumacher, Examples of Hybrid Dynamical Systems, Lecture Notes in Control and Information Sciences, Springer Berlin, Heidelberg, 2000.
T. Manrique, D. Patiño, Mathematical Modelling on Hybrid Dynamical Systems: An Application to the Bouncing Ball and a Two-Tanks System, ANDESCON, IEEE (2010) 1-8.
Y. Hurmuzlu, Dynamics and Control of Bipedal Robots, in: B. Siciliano, K. Valavanis (Eds.), Control Problems in Robotics and Automation, Springer Berlin, Heidelberg, 1998, pp. 105-117.
M. W. Spong, M. Vidyasagar., Robot Dynamics and Control, Wiley, New York, 1989.
R. C. Dorf, R. H. Bishop, Modern Control Systems, ninth ed., Prentice Hall, New Jersey, 2001.
L. T. Dung, H. Kang, Y. Ro. Robot Manipulator Modeling in Matlab-SimMechanics with PD Control and Online Gravity Compensation, Strategic Technology (IFOST), 2010 International Forum on. (2010) 446-449.
O. Haavisto, H. Hyotyniemi, Simulation Tool of a Biped Walking Robot Model, Helsinki University of Technology Control Engineering Laboratory, Report 138, 2004.
E. Kreyszig, Advanced Engineering Mathematics, eighth ed., Wiley, New Jersey, 1999.
R. Wolfson, J. M. Pasachoff, Physics: Extended with Modern Physics, HarperCollins, USA, 1990.
K. M. Passino, S. Yurkovich, Fuzzy Control, Addison-Wesley, Menlo Park, Calif., 1998.
H. B. Kazemian, Intelligent Fuzzy PID Controller, in: A. Verschoren (Ed.), Foundations of Generic Optimization, Springer, Netherlands, 2008, pp. 241-260.
M. Golob, B. Tovornik, Modeling and control of the magnetic suspension system, ISA Transactions, 42 (2003) 89-100.
Z. Yongjuan, P. Yutitan, The Design and Simulation of Fuzzy PID Controller, IFITA, 2010 International Forum on.
Z. Souar, K. Chegrounce, F. Olivie, Comparative Analysis of PI and Fuzzy Logic Controllers for a New Intelligent Control of Speed, (2010) International Review of Automatic Control (IREACO), 3 (1), pp. 53-59.
Š. Kozák, J. Števek, Application of Hybrid Modeling and Control for Air-Handling Unit, (2010) International Review of Automatic Control (IREACO), 3 (3), pp. 317-323.
J. Osuský, S. Števo, Hybrid Control of Water Level in Tank System, (2011) International Review of Automatic Control (IREACO), 4 (6), pp. 977-984.
M. Y. Bejomeh, B. Ganji, A. Z. Kouzani, Evaluation of Analogue PID, Digital PID and Fuzzy Controllers for a Servo System, (2012) International Review of Automatic Control (IREACO), 5 (2), pp. 255-261.
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