Abstract
This manuscript presents a SIMULINK model of Inverted Pendulum (IP) and design of a Fuzzy Logic Controller (FLC) to control of Cart Position (CP), and Angular Position (AP) of the pendulum under uncertainties and disturbances. The FLC is a novel approach whose gains dynamically vary with respect to the error and change in the error signal. The validation of the improved control performance of FLC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better response of the proposed approach to control the system dynamics within the stable range with respect to accuracy, robustness, and ability to handle uncertainties.
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References
Iqbal, J., Islam R, U., Syed, Z.A., Abdul, A.K., Ajwad, S.A.: Automating industrial tasks through mechatronic systems—a review of robotics in industrial perspective. Tehnic ki vjesnik—Tech. Gaz. 23, 917–924 (2016)
Ajwad, S.A., Asim, N., Islam, R.U., Iqbal, J.: Role and review of educational robotic platforms in preparing engineers for industry. Maejo Int. J. Sci. Technol. 11, 17–34 (2017)
Bettayeb, M., Boussalem, C., Mansouri, R., Al-Saggaf, U.: Stabilization of an inverted pendulum-cart system by fractional PI-state feedback. ISA Trans. 53, 508–516 (2014)
Iqbal, J., Ullah, M., Khan, S.G., Khelifa, B., Ukovic, S.C.: Nonlinear control systems -a brief overview of historical and recent advances. Nonlinear Eng. 6, 301–312 (2017)
Ghosh, A., Krishnan, T., Subudhi, B.: Brief paper—robust proportional-integral-derivative compensation of an inverted cart-pendulum system: an experimental study. IET Control Theor. Appl. 6(8), 1145–1152 (2012)
Wang, C., Yin, G., Liu, C., Fu, W.: Design and simulation of inverted pendulum system based on the fractional PID controller. In: IEEE 11th Conference on Industrial Electronics and Applications (ICIEA). pp. 1760–1764 (2016)
Magana, M.E., Holzapfel, F.: Fuzzy-logic control of an inverted pendulum with vision feedback. IEEE Trans. Educ. 41(2), 165–170 (1998)
Ozana, S., Pies, M., Slanina, Z., Hajovsky, R.: Design and implementation of LQR controller for inverted pendulum by use of REX control system. IEEE Int. Conf. Circ. Syst. 1, 343–347 (2012)
Kumar, E.V., Jerome, J.: Robust LQR controller design for stabilizing and trajectory tracking of inverted pendulum. Proc. Eng. 64, 169–178 (2013)
Prasad, L.B., Tyagi, B., Gupta, H.O.: Modelling and simulation for optimal control of nonlinear inverted pendulum dynamical system using PID controller and LQR. In: 6th Asia, Modelling Symposium (Ams), pp. 138–143 (2012)
Pasemann, F.: Evolving neurocontrollers for balancing an inverted pendulum. Netw. Comput. Neural Syst. 9, 1–4 (1998)
Deng, L., Gao, S.: The design for the controller of the linear inverted pendulum based on backstepping. Int. Conf. Electron. Mech. Eng. Inf. Technol. (EMEIT). 6, 2892–2895 (2011)
Jörgl, M., Schlacher, K., Gattringer, H.: Passivity based control of a cart with inverted pendulum. Appl. Mech. Mater. 332, 339–344 (2013)
Žilić, T., Pavković, D.: Modeling and control of a pneumatically actuated inverted pendulum. ISA Trans. 48, 327–335 (2009)
Lambrecht, P., Vander, G.: H-infinity control of an experimental inverted pendulum with dry friction. IEEE Contr. Syst. Mag. 13(4), 44–50 (1988)
Wai, R.J., Chang, L.J.: Adaptive stabilizing and tracking control for a nonlinear inverted-pendulum system via sliding-mode technique. IEEE Trans. Ind. Electron. 53, 674–692 (2006)
Tao, C.W., Taur, J., Chang, J.: Adaptive fuzzy switched swing-up and sliding control for the double-pendulum-and-cart system. IEEE Trans. Syst. Man Cybern. B Cybern. 40(1), 241–252 (2010)
Chen, C.S., Chen, W.L.: Robust adaptive sliding-mode control using fuzzy modelling for an inverted-pendulum system. IEEE Trans. Ind. Electron. 45(2), 297–306 (1998)
Patra, A.K., Rout, P.K.: Backstepping linear quadratic gaussian controller design for balancing an inverted pendulum. IETE J. Res. 1, 1–15 (2019)
Khalil, H.K.: Nonlinear Systems, 3rd edn. Prentice Hall, Upper Saddle River, New Jersey (2002)
Patra, A.K., Rout, P.K.: Adaptive sliding mode Gaussian controller for artificial pancreas in TIDM patient. J. Process Control 58, 23–27 (2017)
Patra, A.K., Rout, P.K.: Backstepping sliding mode Gaussian insulin injection control for blood glucose regulation in TIDM patient. J. Dyn. Sys. Meas. Control. 140(9): 091006-091006-15 (2018)
Irfan, S., Mehmood, A., Razzaq, M.T., Iqbal, J.: Advanced sliding mode control techniques for inverted pendulum: modelling and simulation. Eng. Sci. Tech., Int. J. https://doi.org/10.1016/j.jestch.2018.06.010 (2018)
Ronquillo-Lomeli, G., Ríos-Moreno, G.J.: Nonnlinear identification of inverted pendulum system using Volterra polynomials. Mech. Based Des. Struct. Mach. 44(1), 5–15 (2016)
Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K.: Biped walking pattern generation by a simple three-dimensional inverted pendulum model. Adv. Robot. 17(2), 131–147 (2003)
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Patra, A.K., Mishra, A.K., Agrawal, R., Nahak, N. (2021). Stabilizing and Trajectory Tracking of Inverted Pendulum Based on Fuzzy Logic Control. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 194. Springer, Singapore. https://doi.org/10.1007/978-981-15-5971-6_59
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