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Relevant bibliographies by topics / CART POLE SYSTEM

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Journal articles

Academic literature on the topic 'CART POLE SYSTEM'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "CART POLE SYSTEM"

1

Jia, Hong Li, Qiang Liu, and Feng Du. "Intelligent Control of a Cart and Pole System." Applied Mechanics and Materials 397-400 (September 2013): 1438–41. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.1438.

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The paper focuses on the cart-pole system by using fuzzy control, fuzzy mamdan control theory, the fuzzy controller perturbation amplitude simulation and fine-tuning of different linear and nonlinear model. It applicates MATLAB soft which function is so powerful, suitable for a wide range of engineering software system for vehicle simulation intelligent control. And then adjusting fuzzy controller on PID control system, fuzzy control system, the cart-pole system can provide reliable data for our real life and production in the future.

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2

Wang, Yifan. "PD-Based Control of Cart-Pole System on Inclined Plane with Variable Slope." Journal of Physics: Conference Series 2216, no. 1 (2022): 012064. http://dx.doi.org/10.1088/1742-6596/2216/1/012064.

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Abstract For control research, the cart-pole system is one of the basic models. Various controllers for controlling under-actuated systems in unstable postures are available, according to the literature. In this paper, an off-line management of a variable slope cart-pole system is proposed. The system moves on a circular arc surface with a certain radius. The dynamic pattern of the cart-pole system is obtained by Euler-Lagrangian formulation, and the controllability analysis is considered. Initially, a Python model of the proposed system was created, which was then simulated with a PD controller. Based on the required joint angle, we can calculate the required control parameter distribution. By studying the differences in the stability time and steady-state error of the system under different parameters, the efficacy of the suggested method is proved, and the possibility of further parameter optimization is proposed. For the future study, the simulation of a more irregular trajectory would be inspired by this model and control of the cart-pole system on a non-linear trajectory.

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3

Dadios, Elmer P., Patrick S. Fernandez, and David J. Williams. "Genetic Algorithm On Line Controller for the Flexible Inverted Pendulum Problem." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 2 (2006): 155–60. http://dx.doi.org/10.20965/jaciii.2006.p0155.

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This paper presents a real time controller for a highly non-linear system. The Flexible Pole-Cart Balancing Problem (FPCBP) is used as the test case to investigate the learning capability of Genetic Algorithm (GA) in physical application. The controller developed is initially trained using a set of data taken from on line dynamics of the flexible pole cart balancing system. Based from the physical data of the system, the weights W1 to W6 are optimized by the genetic algorithm in order to determine the correct value of the force applied to the cart. The trained GA-based controller then controls the physical Flexible Pole-Cart Balancing system for infinite time. Analysis on the behavior of the GA model developed is presented. Results of the physical experiments show that the controller developed is accurate, adaptive and robust.

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4

Aguilar-Ibáñez, Carlos, Julio Mendoza-Mendoza, and Jorge Dávila. "Stabilization of the cart pole system: by sliding mode control." Nonlinear Dynamics 78, no. 4 (2014): 2769–77. http://dx.doi.org/10.1007/s11071-014-1624-6.

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5

Assefa, Alemie. "Reduced Order Observer Based Pole Placement Design for Inverted Pendulum on Cart." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 3, no. 2 (2022): 1–11. http://dx.doi.org/10.54060/jieee/003.02.002.

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The inverted pendulum is an under actuated system and unstable system without a controller. In this paper modelling of an inverted pendulum is done using the Euler-Lagrange equation for stabilization of it. The controller gain is evaluated through state feedback and reduced-order observer design techniques and the result for the different initial conditions is compared. The state feedback controller is designed by Pole- placement technique for different desired pole locations. The simulation of the inverted pendulum based on reduced order pole placement design has been done on MATLAB/SIMULINK. It has been observed from the simulation result that the angular velocity and cart speed tracks the system response for different initial conditions by varying the desired pole location for the left-hand plane of the s-plane. In general, if some of the systems are unknown and the other state is known we can design using a re-duced-order observer for any physical system.

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6

MATSUURA, Katsumasa, and Mitsuharu NAGAMORI. "An Improvement of Uprising Method of Pole in the Fuzzy Control of Cart-Pole System." Journal of Japan Society for Fuzzy Theory and Systems 8, no. 4 (1996): 749–56. http://dx.doi.org/10.3156/jfuzzy.8.4_157.

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7

Fauziyah, Mila, Zakiyah Amalia, Indrazno Siradjuddin, Denda Dewatama, Rendi Pambudi Wicaksono, and Erni Yudaningtyas. "Linear quadratic regulator and pole placement for stabilizing a cart inverted pendulum system." Bulletin of Electrical Engineering and Informatics 9, no. 3 (2020): 914–23. http://dx.doi.org/10.11591/eei.v9i3.2017.

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The system of a cart inverted pendulum has many problems such as nonlinearity, complexity, unstable, and underactuated system. It makes this system be a benchmark for testing many control algorithm. This paper presents a comparison between 2 conventional control methods consist of a linear quadratic regulator (LQR) and pole placement. The comparison indicated by the most optimal steps and results in the system performance that obtained from each method for stabilizing a cart inverted pendulum system. A mathematical model of DC motor and mechanical transmission are included in a mathematical model to minimize the realtime implementation problem. From the simulation, the obtained system performance shows that each method has its advantages, and the desired pendulum angle and cart position reached.

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8

Nguyen, Hai Van Dong, Tam Minh Nguyen, and Mircea Ivanescu. "A method of sliding mode control of cart and pole system." Science and Technology Development Journal 18, no. 3 (2015): 167–73. http://dx.doi.org/10.32508/stdj.v18i3.898.

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This paper presents a method of using Sliding Mode Control (SMC) for Cart and Pole system. The stability of controller is proved through using Lyapunov function and simulations. A genetic algorithm (GA) program is used to optimize controlling parameters. The GA-based parameters prove good-quality of control through Matlab/Simulink Simulation.

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9

Liu, Yang, Hongnian Yu, Sam Wane, and Taicheng Yang. "On tracking control of a pendulum-driven cart-pole underactuated system." International Journal of Modelling, Identification and Control 4, no. 4 (2008): 357. http://dx.doi.org/10.1504/ijmic.2008.021476.

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10

Li, Tzuu-Hseng S., and Ming-Yuan Shieh. "Switching-type fuzzy sliding mode control of a cart–pole system." Mechatronics 10, no. 1-2 (2000): 91–109. http://dx.doi.org/10.1016/s0957-4158(99)00053-7.

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