Abstract
This manuscript presents a SIMULINK model of inverted pendulum (IP) and design of a linear quadratic regulator (LQR) to control of cart position (CP) and angular position (AP) of the pendulum under uncertainties and disturbances. For designing of the LQR, a fourth-order state-space model of the IP is taken. The LQR is a novel approach whose gains dynamically vary with respect to the error signal. The validation of the improved control performance of LQR 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 RU, Syed ZA, Abdul AK, Ajwad SA (2016) Automating industrial tasks through mechatronic systems—a review of robotics in industrial perspective. Tehnic ki vjesnik – Technical Gazette 23:917–924
Ajwad SA, Asim N, Islam RU, Iqbal J (2017) Role and review of educational robotic platforms in preparing engineers for industry. Maejo Int J Sci Technol 11:17–34
Bettayeb M, Boussalem C, Mansouri R, Al-Saggaf U (2014) Stabilization of an inverted pendulum-cart system by fractional PI-state feedback. ISA Trans 53:508–516
Iqbal J, Ullah M, Khan SG, Khelifa B, Ukovic SC (2017) Nonlinear control systems—a brief overview of historical and recent advances. Nonlinear Eng 6:301–312
Ghosh A, Krishnan T, Subudhi B (2012) Brief paper—robust proportional-integral-derivative compensation of an inverted cart-pendulum system: an experimental study. IET Control Theor Appl 6(8):1145–1152
Wang C, Yin G, Liu C, Fu W (2016) Design and simulation of inverted pendulum system based on the fractional PID controller. In: IEEE 11th conference on industrial electronics and applications (ICIEA), June, pp 1760–1764
Magana ME, Holzapfel F (1998) Fuzzy-logic control of an inverted pendulum with vision feedback. IEEE Trans Educ 41(2):165–170
Ozana S, Pies M, Slanina Z, Hajovsky R (2012) Design and implementation of LQR controller for inverted pendulum by use of REX control system. In: IEEE international conference on circuits and systems, vol 1, pp 343–347
Kumar EV, Jerome J (2013) Robust LQR controller design for stabilizing and trajectory tracking of inverted pendulum. Procedia Eng 64:169–178
Prasad LB, Tyagi B, Gupta HO (2012) Modelling and simulation for optimal control of nonlinear inverted pendulum dynamical system using PID controller and LQR. In: Modelling symposium (Ams), Sixth Asia, pp 138–143
Pasemann F (1998) Evolving neurocontrollers for balancing an inverted pendulum. Netw Comput Neural Syst 9:1–4
Deng L, Gao S (2011) The design for the controller of the linear inverted pendulum based on backstepping. In: International conference on electronic and mechanical engineering and information technology (EMEIT), vol 6, pp 2892–2895
Jörgl M, Schlacher K, Gattringer H (2013) Passivity based control of a cart with inverted pendulum. Appl Mech Mater 332:339–344
Žilić T, Pavković D (2009) Modeling and control of a pneumatically actuated inverted pendulum. ISA Trans 48:327–335
Lambrecht P, Vander G (1988) H-infinity control of an experimental inverted pendulum with dry friction. IEEE Contr Syst Mag 13(4):44–50
Wai RJ, Chang LJ (2006) Adaptive stabilizing and tracking control for a nonlinear inverted-pendulum system via sliding-mode technique. IEEE Trans Ind Electron 53:674–692
Tao CW, Taur J, Chang J (2010) 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
Chen CS, Chen WL (1998) Robust adaptive sliding-mode control using fuzzy modelling for an inverted-pendulum system. IEEE Trans Ind Electron 45(2):297–306
Patra AK, Rout PK (2019) Backstepping linear quadratic gaussian controller design for balancing an inverted pendulum. IETE J Res 1–15
Khalil HK (2002) Nonlinear systems, 3rd edn. Prentice Hall, Upper Saddle River, New Jersey
Patra AK, Rout PK (2017) Adaptive sliding mode Gaussian controller for artificial pancreas in TIDM patient. J Process Control 58:23–27
Patra AK, Rout PK (2018) Backstepping sliding mode Gaussian insulin injection control for blood glucose regulation in TIDM patient. J Dyn Syst Meas Control 140(9):091006–091006-15
Irfan S, Mehmood A, Razzaq MT, Iqbal J (2018) 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
Ronquillo-Lomeli G, RÃos-Moreno GJ (2016) Nonnlinear identification of inverted pendulum system using Volterra polynomials. Mech Based Des Struct Mach 44(1):5–15
Kajita S, Kanehiro F, Kaneko K, Fujiwara K (2003) Biped walking pattern generation by a simple three-dimensional inverted pendulum model. Adv Robot 17(2):131–147
Canete L, Takahashi T (2015) Modeling, analysis and compensation of disturbances during task execution of a wheeled inverted pendulum type assistant robot using a unified controller. Adv Robot 29(22):1453–1462
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Patra, A.K., Mishra, A.K., Nanda, A., Agrawal, R., Patra, A., Barik, S. (2020). Linear Quadratic Regulator Design for Stabilizing and Trajectory Tracking of Inverted Pendulum. In: Sharma, R., Mishra, M., Nayak, J., Naik, B., Pelusi, D. (eds) Innovation in Electrical Power Engineering, Communication, and Computing Technology. Lecture Notes in Electrical Engineering, vol 630. Springer, Singapore. https://doi.org/10.1007/978-981-15-2305-2_30
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DOI: https://doi.org/10.1007/978-981-15-2305-2_30
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