Modeling and control of a pneumatically actuated inverted pendulum

ISA Transactions

Volumn 48, Issue 3, 2009, Pages 327-335

  Žilić, Tihomir ^a   Pavković, Danijel ^a   Zorc, Davor ^a  

^a UNIVERSITY OF ZAGREB   (Croatia)

Author keywords

Friction; Linear Quadratic control; Linear Quadratic Gaussian control; Modeling; Optimization methods; Pneumatic systems

Indexed keywords

FEEDBACK CONTROL; FRICTION; LINEAR CONTROL SYSTEMS; LINEARIZATION; MODELS; NONLINEAR CONTROL SYSTEMS; PENDULUMS; PNEUMATIC CONTROL EQUIPMENT; PNEUMATICS; ROBUSTNESS (CONTROL SYSTEMS); STATE FEEDBACK; STICTION; TRIBOLOGY; VOLTAGE DIVIDERS;

EXPERIMENTAL IDENTIFICATION; LINEAR QUADRATIC CONTROL; LINEAR QUADRATIC GAUSSIAN CONTROL; NONLINEAR FRICTION EFFECTS; OPTIMIZATION METHOD; PNEUMATIC SYSTEM; POSITION MEASUREMENT SYSTEMS; STATE FEEDBACK CONTROLLER;

CONTROLLERS;

ALGORITHM; ARTICLE; ATMOSPHERIC PRESSURE; COMPUTER SIMULATION; FEEDBACK SYSTEM; GRAVITY; QUALITY CONTROL; THEORETICAL MODEL;

AIR PRESSURE; ALGORITHMS; COMPUTER SIMULATION; FEEDBACK; GRAVITATION; MODELS, THEORETICAL; QUALITY CONTROL;

EID: 67349181030     PISSN: 00190578     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isatra.2009.03.004     Document Type: Article

References (30)

1. Shiroma N, Matsumoto O, Kajita S, Tani K. Cooperative behavior of a wheeled inverted pendulum for object transportation. In: Proceedings of the 1996 IEEE/RSJ international conference on intelligent robots and systems, vol. 2. 1996. p. 390-5
2. Shimada A, Hatakeyama N. High-speed motion control of wheeled inverted pendulum robots. In: Proceedings of international conference on mechatronics. 2007. 6 pages
3. Zveu KV, Shipitko EA, Perevozchikov AS. Linear neural model-based predictive controller design for flexible link robot. In: Proceedings of the 2004 international symposium on intelligent control. 2004. p. 293-8
4. Kuo A.D. The six determinants of gait and the inverted pendulum analogy: A dynamic walking perspective. Human Movement Science 26 (2007) 617-656
5. Vanderborght B., Verrelst B., Van Ham R., Van Damme M., and Lefeber D. Objective locomotion parameter based inverted pendulum trajectory generator. Robotics and Autonomous Systems 56 (2008) 738-750
6. Hauser J, Saccon A, Frezza R. On the driven inverted pendulum. In: Proceedings of the 44th IEEE conference on decision and control, and the European control conference. 2005. p. 6176-80
7. Nundrakwang S, Benjanarasuth T, Ngamwiwit J, Komine N. Hybrid controller for swinging up inverted pendulum system, In: Proceedings of the 2005 fifth international conference on information, communications and signal processing. 2005. p. 488-92
8. Miyagawa T, Ishida Y. Neural network-based model reference control for inverted pendulum. In: Proceedings of the 1995 IEEE international conference on neural networks. vol. 1. 1995. p. 640-4
9. Chen X, Zhou H, Ma R, Zuo F, Zhai G, Gong M. Linear motor driven inverted pendulum and lqr controller design. In: Proceedings of the IEEE international conference on automation and logistics. 2007. p. 1750-4
10. Cui P., Weng Z., and Patton R. Novel active fault-tolerant control scheme and its application to a double inverted pendulum system. Journal of Systems Engineering and Electronics 19 1 (2008) 134-140
11. Nikkah M, Ashrafion H, Muske KR. Optimal sliding mode control for underactuated systems. In: Proceedings of the 2006 American control conference. 2006. p. 4688-93
12. Chen C.S., and Chen W.L. Robust adaptive sliding mode control using fuzzy modeling for an inverted-pendulum system. IEEE Transactions on Industrial Electronics 45 2 (1998)
13. Wai R.J., and Chang L.J. Adaptive stabilizing and tracking control for a nonlinear inverted-pendulum system via sliding-mode technique. IEEE Transactions on Industrial Electronics 53 2 (2006)
14. Ronco E, Arsan T, Gawthrop PJ, Hill DJ. A globally valid continuous-time GPC through successive system linearizations. In: Proceedings of the 38th conference on decision and control. vol. 1. 1999. p. 726-31
15. Cipriano A, Saez D. Fuzzy generalized predictive controller and its application to an inverted pendulum. In: Proceedings of the 1996 IEEE IECON 22nd international conference on industrial electronics, control and instrumentation. vol. 3. 1996. p. 1966-71
16. Lizarralde F, Wen JT, Hsu L. A new model predictive control strategy for affine nonlinear control. In: Proceedings of the 1999 American control conference. vol. 6. 1999. p. 4263-7
17. Magni L., and Scattolini R. Stabilizing model predictive control of nonlinear continuous time systems. Annual Reviews in Control vol. 28 (2004), Elsevier 1-11
18. Williams V, Matsuoka K. Learning to balance the inverted pendulum using neural networks. In: Proceedings of the 1991 joint conference on neural networks. vol. 1. 1991. p. 214-9
19. Marzi H. Fuzzy control of an inverted pendulum using AC induction motor actuator. In: Proceedings of the 2006 IEEE international conference on computational intelligence for measurement systems and applications, 2006. p. 109-14
20. Mrad F, El-Hassan N, El-Haj Mahmoud S, Alawieh B, Adlouni F. Real-time control of free-standing cart-mounted inverted pendulum using LabVIEW RT. In: Conference record of 2000 IEEE industry applications conference. vol. 2. 2000. p. 1291-8
21. Wai R.J., and Chang L.J. Stabilizing and tracking control for a nonlinear dual-axis inverted-pendulum system using fuzzy neural network. IEEE Transactions on Fuzzy Systems 14 1 (2006)
22. Huang S.J., and Huang C.L. Control of an inverted pendulum using grey prediction model. IEEE Transactions on Industry Applications 36 2 (2000)
23. Šitum Ž., Pavković D., and Novaković B. Servo pneumatic position control using fuzzy PID gain scheduling. Journal of Dynamic Systems, Measurement and Control-Transactions of the ASME 126 (2004) 376-387
24. Festo AG. Proportional directional control valves MYPE. 06/2008. http://www.festo.com
25. Beater P. Pneumatic drives-system design, modeling and control (2007), Springer-Verlag, Berlin (Heidelberg)
26. Armstrong-Hélouvry B., Dupont P., and Canudas De Wit C. A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica 30 7 (1994) 1083-1138
27. Anderson B.D.O., and Moore J.B. Optimal control-linear quadratic methods (1989), Prentice Hall Inc, Englewood Cliffs, New Jersey
28. Aström K.J., and Wittenmark B. Computer controlled systems (1984), Prentice-Hall, London
29. Bryson A.E., and Ho Y.C. Applied optimal control (1969), Blaisdell Publishing Co, Waltham (MA)
30. Brandeburg G, Schäfer U. Influence and compensation of columb friction in industrial pointing and tracking system. In: Proceedings of the IEEE industry application society annual meeting. 1991. p.1407-13