Experimental investigations of mechanical and reaction responses for drop-weight impacted energetic particles 
期刊名称Acta Mechanica Sinica
作者Fabian Schnelle; Peter Eberhard
摘要This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in threedimensional space.
关键词Model predictive control; Feedback linearization; Unscented Kalman filter; Flexible-link manipulator; Fuzzy-arithmetical analysis
参考文献1. Devasia, S., Chen, D., Paden, B.:Nonlinear inversion-based output tracking.IEEE Trans.Autom.Control 41, 930-942(1996)  
2. Luca, A.D., Siciliano, B.:Inversion-based nonlinear control of robot arms with flexible links.J.Guid.Control Dyn.16, 1169-1176(1993)  
3. Isidori, A.:Nonlinear Control Systems.Springer, London (1995)
4. Sastry, S., Isidori, A.:Adaptive control of linearizable systems.IEEE Trans.Autom.Control 34, 1123-1131(1989)  
5. Slotine, J.-J.E., Hedrick, J.K.:Robust input-output feedback linearization.Int.J.Control 57, 1133-1139(1993)  
6. Slotine, J.-J.E., Li, W.:On the adaptive control of robot manipulators.Int.J.Rob.Res.6, 49-59(1987)  
7. Sage, H., De Mathelin, M., Ostertag, E.:Robust control of robot manipulators:a survey.Int.J.Control 72, 1498-1522(1999)  
8. Morari, M., Lee, J.H.:Model predictive control:past, present and future.Comput.Chem.Eng.23, 667-682(1999)  
9. Qin, S.J., Badgwell, T.A.:A survey of industrial model predictive control technology.Control Eng.Pract.11, 733-764(2003)  
10. Hedjar, R., Boucher, P.:Nonlinear receding-horizon control of rigid link robot manipulators.Int.J.Adv.Rob.Syst.2, 15-24(2005)  
11. Boscariol, P., Gasparetto, A., Zanotto, V.:Model predictive control of a flexible links mechanism.J.Intell.Rob.Syst.58, 125-147(2010)  
12. Hassan, M., Dubay, R., Li, C., et al.:Active vibration control of a flexible one-link manipulator using a multivariable predictive controller.Mechatronics 17, 311-323(2007)  
13. Bossi, L., Rottenbacher, C., Mimmi, G., et al.:Multivariable predictive control for vibrating structures:an application.Control Eng.Pract.19, 1087-1098(2011)  
14. Bemporad, A., Morari, M.:Robust model predictive control:a survey.In:Robustness in Identification and Control.Springer, 207-266(1999)
15. Fukushima, H., Kim, T.-H., Sugie, T.:Adaptive model predictive control for a class of constrained linear systems based on the comparison model.Automatica 43, 301-308(2007)  
16. Chowdhary, G., Mühlegg, M., How, J.P., et al.:Concurrent learning adaptive model predictive control.In:Advances in Aerospace Guidance, Navigation and Control, Springer, 29-47(2013)
17. Takacs, G., Poloni, T., Rohal-Ilkiv, B.:Adaptive model predictive vibration control of a cantilever beam with real-tme parameter estimation.Shock Vib.2014, 1-15(2014)
18. Pradhan, S.K., Subudhi, B.:Nonlinear adaptive model predictive controller for a flexible manipulator:an experimental study.IEEE Trans.Control Syst.Technol.22, 1754-1768(2014)  
19. Hanss, M.:Applied Fuzzy Arithmetic-An Introduction with Engineering Applications.Springer, Berlin (2005)
20. Shabana, A.:Flexible multibody dynamics:review of past and recent developments.Multibody Syst.Dyn.1, 189-222(1997)  
21. Lehner, M.:Modellreduktion in elastischen mehrkörpersystemen.[Ph.D.Thesis], Schriften aus dem Institut für Technische und Numerische Mechanik der Universität Stuttgart, Vol.10, Shaker Verlag, Aachen (in German)(2007)
22. Wallrapp, O.:Standardization of flexible body modeling in multibody system codes, part I:definition of standard input data.Mech.Struct.Mach.22, 283-304(1994)  
23. Blajer, W., Kołodziejczyk, K.:A geometric approach to solving problems of control constraints:theory and a dae framework.Multibody Syst.Dyn.11, 343-364(2004)  
24. Altmann, R., Betsch, P., Yang, Y.:Index reduction by minimal extension for the inverse dynamics simulation of cranes.Multibody Syst.Dyn.11, 295-321(2016)
25. Seifried, R., Burkhardt, M., Held, A.:Trajectory control of flexible manipulator using model inversion.In:Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2011, Belgium, Brussels (2011)
26. Seifried, R.:Dynamics of Underactuated Multibody Systems-Modeling, Control and Optimal Design:Analysis, Stability and Control.Springer, Berlin (2014)
27. Sastry, S.:Nonlinear Systems:Analysis, Stability and Control.Springer, New York (1999)
28. Maciejowski, J.M.:Predictive Control with Constraints.Prentice Hall, Upper Saddle River (2002)
29. Kurtz, M.J., Henson, M.A.:Input-output linearizing control of constrained nonlinear processes.J.Process Control 7, 3-17(1997)  
30. Schnelle, F., Eberhard, P.:Constraint mapping in a feedback linearization/mpc scheme for trajectory tracking of underactuated multibody systems.In:Proceedings of the 5th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2015), Seville, 446-451(2015)
31. Schnelle, F., Eberhard, P.:Adaptive model predictive control design for underactuated multibody systems with uncertain parameters.In:ROMANSY 21-Robot Design, Dynamics and Control, Springer, 145-152(2016)
32. Wan, E., Van Der Merwe, R.:The unscented Kalman filter for nonlinear estimation.In:Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000.AS-SPCC.The IEEE 2000, 153-158(2000)
33. Julier, S.J., Uhlmann, J.K.:New extension of the Kalman filter to nonlinear systems.In:AeroSense'97, International Society for Optics and Photonics, 182-193(1997)
34. Walz, N.-P., Hanss, M.:Fuzzy arithmetical analysis of multibody systems with uncertainties.Arch.Mech.Eng.60, 109-125(2013)
35. Wasfy, T.M., Noor, A.K.:Finite element analysis of flexible multibody systems with fuzzy parameters.Comput.Methods Appl.Mech.Eng.160, 223-243(1998)  
36. Walz, N.-P., Burkhardt, M., Eberhard, P., et al.:A comprehensive fuzzy uncertainty analysis of a controlled nonlinear system with unstable internal dynamics.ASCE ASME J.Risk Uncertain.Eng.Syst.Part B Mech.Eng.1, 041008(2015)  
37. Zadeh, L.A.:Fuzzy sets.Inf.Control 8, 338-353(1965)  
38. Hanss, M.:The transformation method for the simulation and analysis of systems with uncertain parameters.Fuzzy Sets Syst.130, 277-289(2002)  
39. Gauger, U., Turrin, S., Hanss, M., et al.:A new uncertainty analysis for the transformation method.Fuzzy Sets Syst.159, 1273-1291(2008)  
40. Lee, C.-C.:Fuzzy logic in control systems:fuzzy logic controller.Ⅱ.IEEE Trans.Syst.Man Cybern.20, 419-435(1990)
作者地址Institute of Engineering and Computational Mechanics, University of Stuttgart, 70569 Stuttgart, Germany

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