Nonlinear Model Predictive Swing-Up and Stabilizing Sliding Mode Controllers
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Nonlinear Model Predictive Swing-Up and Stabilizing Sliding Mode Controllers

Authors: S. Kahvecioglu, A. Karamancioglu, A. Yazici

Abstract:

In this paper, a nonlinear model predictive swing-up and stabilizing sliding controller is proposed for an inverted pendulum-cart system. In the swing up phase, the nonlinear model predictive control is formulated as a nonlinear programming problem with energy based objective function. By solving this problem at each sampling instant, a sequence of control inputs that optimize the nonlinear objective function subject to various constraints over a finite horizon are obtained. Then, this control drives the pendulum to a predefined neighborhood of the upper equilibrium point, at where sliding mode based model predictive control is used to stabilize the systems with the specified constraints. It is shown by the simulations that, due to the way of formulating the problem, short horizon lengths are sufficient for attaining the swing up goal.

Keywords: Inverted pendulum, model predictive control, swingup, stabilization.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1327847

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[1] R.N. Gasimov, A. Karamancioglu, and A. Yazici, "A nonlinear programming approach for the sliding mode control design," Applied Mathematical Modeling, vol. 29, pp. 1135-1148, 2005.
[2] K. J. Aström and K. Furuta, "Swinging up a pendulum by energy control," Automatica, vol. 36, pp. 287-295, 2000.
[3] A. S. Shiriaev, "VSS-version of energy-based control for swinging up a pendulum," Systems and Control Letters, vol. 44, pp. 45-56, 2001.
[4] K. Yoshida, "Swing-up control of an inverted pendulum by energybased methods," in 1996 Proc. American Control Conference, San Diego, California.
[5] D. Chatterjee, A. Patra, and H. K. Joglekar, "Swing-up and stabilization of a cart-pendulum system under restricted cart track length," Systems and Control Letters, vol. 47, pp. 355-364, 2002.
[6] N. Muskinja and B. Tovornik, "Swinging up and stabilization of a real inverted pendulum," IEEE Trans. Industrial Electronics, vol. 53, pp. 631-639, 2006.
[7] R. Lozano, I. Fantoni, and D. J. Block, "Stabilization of the inverted pendulum around its homoclinic orbit," Systems and Control Letters, vol. 40, pp. 197-204, 2000.
[8] J. Yi, N. Yubazaki, and K. Hirota, "Upswing and stabilization control of inverted pendulum system based on SIRMs dynamically connected fuzzy inference model," Fuzzy Sets and Systems, vol. 122, pp. 139-152, 2001.
[9] E. Mosca, Optimal, Predictive and Adaptive Control, Prentice-Hall, 1994.
[10] E. F. Camacho and C. Bordons, Model Predictive Control, Springer Verlag, 1999.
[11] J. B. Rawlings, "Tutorial overview of model predictive control," IEEE Control Systems Magazine, pp. 38-52, June 2000.
[12] S. J. Quin and T. A. Badgwell, "A survey of industrial model predictive control technology," Control Engineering Practice, pp. 733-764, 2003.
[13] P. Tatjewski and M. Lawrynczuk, "Soft computing in model-based predictive control", International Journal of Applied Mathematics and Computer Science, vol. 16, pp. 7-26, 2006.
[14] C. Onnen, R. Babushka, U. Kaymak, J. M. Sousa, H. B. Verbruggen, and R. Isermann, "Genetic algorithms for optimization in predictive control," Control Engineering Practice, pp. 1363-1372, 1997.
[15] K. Ogata, Modern Control Engineering, Prentice Hall, 1990.
[16] K. Sakurama, S. Hara and K. Nakano, "Swing-up and stabilization of a cart-pendulum system via energy control and controlled lagrangian methods," Electrical Engineering in Japan, vol. 160, pp. 24-31, 2007.
[17] R. A. DeCarlo, S. H. Zak and G. B. Matthews, "Variable structure control of nonlinear multivariable systems: A tutorial", in 1998 Proc. IEEE, vol. 76, pp. 212-232