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Journal articles on the topic 'INVERTED PENDULUM SYSTEM'

Author: Grafiati
Published: 11 September 2023

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1

Nasim, Shahzad, M. Javeed, M. Shafiq, Faraz Liaquat, and Zain Anwar Ali. "Self-Erected Inverted Pendulum." Advanced Materials Research 816-817 (September 2013): 415–19. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.415.

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The basic theme of this research paper is self-erecting the inverted pendulum by via ARDUINO controller and stabilizes the system through PID algorithm of linear control system. ARDUINO controller acquires the data from the sensors in terms of position and angle of the pendulum and commands the motor through PWM signal after that swing the pendulum from rest position to get and balance the inverted position. Controller read the pendulums angular position through potentiometer then calculates and removes errors via PID algorithm. MATLAB-Simulink and LABVIEW sent and receives runtime information from controller.
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2

Mesa, F., R. Ospina Ospina, and D. M. Devia-Narvaez. "Methodology of robust inverted pendulum controllers on a vehicle." Journal of Physics: Conference Series 2102, no. 1 (November 1, 2021): 012012. http://dx.doi.org/10.1088/1742-6596/2102/1/012012.

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Abstract In the theory of controllers, the simple and inverted pendulum play an important role due to the equations that result from them, which imply non-linearities and perturbations, thus, in this article, a brief classification of inverted pendulums is presented: inverted pendulum, inverted double pendulum, inverted rotary pendulum (Furuta pendulum). Subsequently, a mathematical model of the inverted pendulum is described through the deduction of the equations of motion that represent the dynamics of the system. Robust control is presented that allows expanding the richness of the mathematical equations, for this case, a control with output feedback is presented and applied to the inverted pendulum to control the unstable dynamics of this model. The results are compared with a post placement control and a robust control using a norm that analyses the characteristics of the system.
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3

Wang, Yujue, Weining Mao, Qing Wang, and Bin Xin. "Fuzzy Cooperative Control for the Stabilization of the Rotating Inverted Pendulum System." Journal of Advanced Computational Intelligence and Intelligent Informatics 27, no. 3 (May 20, 2023): 360–71. http://dx.doi.org/10.20965/jaciii.2023.p0360.

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The rotating inverted pendulum is a nonlinear, multivariate, strongly coupled unstable system, and studying it can effectively reflect many typical control problems. In this paper, a parameter self-tuning fuzzy controller is proposed to perform the balance control of a single rotating inverted pendulum. Particle swarm optimization is used to adjust its control parameters, and simulation experiments are performed to show that the system can achieve stability with the designed parametric self-tuning fuzzy controller, with control performance better than that of the conventional fuzzy controller. Furthermore, the leader-follower control strategy is used to realize the cooperative control of multiple rotating inverted pendulums. Two QUBE-Servo 2 rotating inverted pendulums are used for a cooperative pendulum swing-up experiment and stabilization experiment, and the effectiveness of the proposed cooperative control strategy is verified.
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4

PAGANO, DANIEL, LUIS PIZARRO, and JAVIER ARACIL. "LOCAL BIFURCATION ANALYSIS IN THE FURUTA PENDULUM VIA NORMAL FORMS." International Journal of Bifurcation and Chaos 10, no. 05 (May 2000): 981–95. http://dx.doi.org/10.1142/s0218127400000700.

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Inverted pendulums are very suitable to illustrate many ideas in automatic control of nonlinear systems. The rotational inverted pendulum is a novel design that has some interesting dynamics features that are not present in inverted pendulums with linear motion of the pivot. In this paper the dynamics of a rotational inverted pendulum has been studied applying well-known results of bifurcation theory. Two classes of local bifurcations are analyzed by means of the center manifold theorem and the normal form theory — first, a pitchfork bifurcation that appears for the open-loop controlled system; second, a Hopf bifurcation, and its possible degeneracies, of the equilibrium point at the upright pendulum position, that is present for the controlled closed-loop system. Some numerical results are also presented in order to verify the validity of our analysis.
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5

Sultan, Ghassan A., and Ziyad K. Farej. "Design and Performance Analysis of LQR Controller for Stabilizing Double Inverted Pendulum System." Circulation in Computer Science 2, no. 9 (October 20, 2017): 1–5. http://dx.doi.org/10.22632/ccs-2017-252-45.

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Double inverted pendulum (DIP) is a nonlinear, multivariable and unstable system. The inverted pendulum which continually moves toward an uncontrolled state represents a challenging control problem. The problem is to balance the pendulum vertically upward on a mobile platform that can move in only two directions (left or right) when it is offset from zero stat. The aim is to determine the control strategy that deliver better performance with respect to pendulum's angles and cart's position. A Linear-Quadratic-Regulator (LQR) technique for controlling the linearized system of double inverted pendulum model is presented. Simulation studies conducted in MATLAB environment show that the LQR controller are capable of controlling the multi output double inverted pendulum system. Also better performance results are obtained for controlling heavy driven part DIP system.
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6

Chawla, Ishan, and Ashish Singla. "ANFIS based system identification of underactuated systems." International Journal of Nonlinear Sciences and Numerical Simulation 21, no. 7-8 (November 18, 2020): 649–60. http://dx.doi.org/10.1515/ijnsns-2018-0005.

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AbstractIn this work, the effectiveness of the adaptive neural based fuzzy inference system (ANFIS) in identifying underactuated systems is illustrated. Two case studies of underactuated systems are used to validate the system identification i. e., linear inverted pendulum (LIP) and rotary inverted pendulum (RIP). Both the systems are treated as benchmark systems in modeling and control theory for their inherit nonlinear, unstable, and underactuated behavior. The systems are modeled with ANFIS using the input-output data acquired from the dynamic response of the nonlinear analytical model of the systems. The dynamic response of the ANFIS model is simulated and compared to the nonlinear mathematical model of the inverted pendulum systems. In order to check the effectiveness of the ANFIS model, mean square error is used as the performance index. From the obtained simulation results, it has been perceived that the ANFIS model performed satisfactorily within the trained operating range while a minor deviation is seen outside the trained operating region for both the case studies. Furthermore, the experimental validation of the of the proposed ANFIS model is done by comparing it with the experimental model of the rotary inverted pendulum. The obtained results show that the response of ANFIS model is in close agreement to the experimental model of the rotary inverted pendulum.
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7

Wang, Hong Qi. "Dynamics Modeling of the Planar Double Inverted Pendulum." Applied Mechanics and Materials 195-196 (August 2012): 17–22. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.17.

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planar double inverted pendulum is a strong coupling, uncertain and complex nonlinear system, and the dynamics model of which is the basis of control, simulation and analysis. In the paper coordinate systems of the planar double inverted pendulum were first defined, and then the dynamics model of which was built up based on screw theory and the Lagrange principle. The modeling method used being systematic and standardized, it is easy to extend to dynamics modeling of higher order planar inverted pendulums or other multi-body systems.
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8

Sun, Qian Lai, and Zhi Yi Sun. "A Simple Control Strategy to Stabilize an Inverted Pendulum System." Advanced Materials Research 433-440 (January 2012): 3997–4002. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3997.

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A simple control strategy is presented to control An inverted pendulum. The control strategy is obtained via mathematical derivation based on the dynamical model of the inverted pendulum system. That control law is simple and independent of the model of the controlled plant. It is applicable for the multi input single output systems similar to inverted pendulum systems. A controller based on that method was designed to control an inverted pendulum. The structure of the controller is simple. And the parameter adjusting is relatively easy. Then the simulation study was realized. The simulation result shows that control law is valid for the inverted pendulum system.
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9

Lastomo, Dwi, Herlambang Setiadi, and Muhammad Ruswandi Djalal. "Design Controller of Pendulum System using Imperialist Competitive Algorithm." INTEK: Jurnal Penelitian 4, no. 1 (May 3, 2017): 53. http://dx.doi.org/10.31963/intek.v4i1.94.

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Due to development of technology in recent years, complexity and nonlinearity of mechanical and electrical system are increasing significantly. Inverted pendulum is nonlinear system that has become popular in recent years. However, inverted pendulum is nonlinear and unstable system. Therefore appropriate design controller of inverted pendulum system is crucial. Hence, this paper proposed, design of inverted pendulum system based on imperialist competitive algorithm (ICA). In order to design the controller, dynamic model of inverted pendulum system is used. Time domain simulation is used to address the controller performance. From the simulation result, it is found that imperialist competitive algorithm can be used to design inverted pendulum system controller.
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10

Samiee, Ahmad. "Optimal Control Comparisons on a Flywheel Based Inverted Pendulum." Mapta Journal of Mechanical and Industrial Engineering (MJMIE) 3, no. 1 (April 20, 2019): 18–26. http://dx.doi.org/10.33544/mjmie.v3i1.108.

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This paper introduces a comparison between two optimal controllers on a flywheel-based inverted pendulum. Inverted pendulums have an essential place in developing under-actuation nonlinear control schemes due to their nonlinear structure. This system is a basic structure for many advanced systems such as biped and mobile wheeled robots. Optimal controllers addressed in this paper consist of State-Dependent Riccati Equation (SDRE) and Linear Quadratic Regulator (LQR). A Proportional–Integral–Derivative controller (PID) is also designed and tested in the simulation. One axis self-balancing flywheel based inverted pendulum system is designed to validate the controllers' performance on an experimental setup.
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11

Cao, Xu, Nian Feng Li, and Hua Xun Zhang. "Robust Controller Design for Inverted Pendulum System." Advanced Materials Research 631-632 (January 2013): 1342–47. http://dx.doi.org/10.4028/www.scientific.net/amr.631-632.1342.

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For the high order, unstable, multivariable, nonlinear and strong coupling characteristics, robust stability is an important indicator of inverted pendulum system. In this paper an LQR robust controller of inverter pendulum system is designed. The simulation and the experimental results showed that the stability of the robust LQR controller is better than the original LQR controller. When the system departure counterpoise for all kinds of reasons, it get back equilibrium state without depleting any energy, and approach state of equilibrium of all state component.
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12

Fitria, Trisonia, Wipsar Sunu Brams Dwandaru, Warsono, R. Yosi Aprian Sari, Dian Puspita Eka Putri, and Adiella Zakky Juneid. "Application Of Inverted Pendulum in Laplace Transformation of Mathematics Physics." Jurnal Penelitian Pendidikan IPA 9, no. 7 (July 25, 2023): 5446–52. http://dx.doi.org/10.29303/jppipa.v9i7.2953.

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The Laplace transform is a technique used to convert differential equations into algebra, it is often used for the analysis of dynamic systems and inverted pendulum systems. An inverted pendulum is a mechanism that moves objects from one place to another and shows the function of its activity while walking. This system is widely used in various fields, for example in the fields of robotics, industry, technology and organics. In an inverted pendulum there is an inverted pendulum dynamic system with a reading and driving force. The results of the study show that using the Laplace transform can make it easier to find solutions regarding the inverted pendulum system for a variety of conditions, both in the initial conditions and when given an additional force or load. The application of the Laplace transform is useful for understanding how an inverted pendulum system will react to various forces, loads and initial conditions, which can be used to predict how the system will operate in the real world
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13

Zhang, Jiao Long, and Wei Zhang. "Adaptive Fuzzy Sliding Mode Control for Uncertain Inverted Pendulum System." Applied Mechanics and Materials 273 (January 2013): 683–88. http://dx.doi.org/10.4028/www.scientific.net/amm.273.683.

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Firstly, the mathematical model of inverted pendulum system is created. Taking into account the uncertainty of inverted pendulum system external disturbances, adaptive fuzzy sliding mode controller is proposed with sliding mode control (SMC) theory and fuzzy logic theory. This controller can weaken the impact of uncertainty through fuzzification of the switching gain, Owing to Fuzzy approximation of the inverted pendulum system equations for an inverted pendulum with unknown parameters, this system achieve the adaptive control and optimize the control action. Secondly, inverted pendulum system has the features which SMC can keep invariance to the external disturbance and parameter perturbation. Lyapunov function is used to prove the stability of the controller. Simulation results also show that this controller can ensure inverted pendulum system fast response and robustness in the SIMULINK conditions.
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14

Gao, Qiang, and Yi Li. "Generalized Predictive Control for Rotary Inverted Pendulum System." Applied Mechanics and Materials 130-134 (October 2011): 4256–60. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.4256.

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Inverted pendulum system is a complex, multivariable, nonlinear, strong-coupling, unstable system of high order. Compared with the straight-line inverted pendulum, rotary inverted pendulum is more complicated and unstable. In this paper, the mathematic model of a rotary inverted pendulum system is analyzed and deduced detailedly by applying the Lagrange method; the control properties and characteristics of generalized predictive control are researched with matlab simulation. Finally, the results of the experiment prove the system controlled by GPC has a better stability and quickness.
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15

Li, Wen Ping, and Li Qiang Wu. "Synthesized ADRC for One-Level Inverted Pendulum System through Combination of Separating and Assembling." Applied Mechanics and Materials 490-491 (January 2014): 794–97. http://dx.doi.org/10.4028/www.scientific.net/amm.490-491.794.

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Inverted pendulum system is the ideal study object of nonlinear system. The ADRC has good estimate for disturbances, strong robustness and using static decoupling instead of dynamical decoupling. The one-level inverted pendulum system can be regarded as composing of the pendulum angel system and the cart position system. The former is faster and the later is slower. The synthesized ADRC for one-level inverted pendulum system is built through combination of separating and assembling to reduce difficulty in optimizing ADRC parameters of the inverted pendulum system. The synthesized controller is simulated by Matlab under different parameters of the inverted pendulum. Simulation results show that the pendulum angle and the cart position are well controlled.
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16

Kao, Sho-Tsung, and Ming-Tzu Ho. "Balance Control of a Configurable Inverted Pendulum on an Omni-Directional Wheeled Mobile Robot." Applied Sciences 12, no. 20 (October 13, 2022): 10307. http://dx.doi.org/10.3390/app122010307.

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This paper considers the balance control problems of a configurable inverted pendulum with an omni-directional wheeled mobile robot. The system consists of two parts. One is an inverted pendulum, and another one is an omni-directional wheeled mobile robot. The system can be configured as a rotary inverted pendulum or a spherical inverted pendulum. The objective is to control the omni-directional wheeled mobile robot to provide translational force on the plane to balance the spherical inverted pendulum and to provide the moment to balance the rotary inverted pendulum. Detailed dynamic models of these two systems are derived for the control strategy design and simulation studies. Stabilizing controllers based on the second-order sliding mode control are designed for both systems. The closed-loop stability is proved based on the passivity properties. The proposed control schemes can guarantee semi-globally asymptotical stability over the upper-half plane. In addition, the conventional sliding mode controllers proposed in our previous work and Linear-Quadratic Regulator (LQR) controllers based on the linearized system models about its upright equilibrium point are also used for performance comparison. The effectiveness of the control strategies is investigated and verified using simulation and experimental studies. In the simulation studies, different sources of uncertainty and disturbance are investigated. It is shown that the second-order sliding mode control outperforms the conventional sliding mode control and LQR control without any uncertainty and disturbance. For robustness to the matched disturbance, the simulation results show that the second-order sliding mode controller has a less significant steady-state oscillation in the pendulum’s angular displacement than other controllers. The simulation results also show that only the second-order sliding mode controller can stabilize the system with a significant initial deviation from the pendulum’s upright position. Finally, the experimental results demonstrate that second-order sliding mode control outperforms conventional sliding mode control and LQR control.
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17

Ou, Qun Yong. "The Design of Real-Time Control System Based on Single-Inverted Pendulum." Advanced Materials Research 850-851 (December 2013): 553–56. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.553.

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An inverted pendulum is a classic control problem and is widely used as a benchmark for testing various control algorithms. First, this paper analyse the dynamic and non-linear model of the inverted pendulum, then focus on the real-time control of the inverted pendulum, we developed real-time control software for the single-stage inverted pendulum by using Visual C++ 2010, its mainly operate API functions to control board and implement various control algorithms.
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18

Qi, Han. "Application of Fuzzy Control Algorithm in First-order Inverted Pendulum System." Journal of Physics: Conference Series 2417, no. 1 (December 1, 2022): 012038. http://dx.doi.org/10.1088/1742-6596/2417/1/012038.

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The inverted pendulum system is widely used in the study of control theory. There are many advantages of the inverted pendulum: the equipment is cheap, and it features a simple structure and easy regulation. But since the inverted pendulum system is also a typical nonlinear, multivariable system, it’s a really difficult thing to keep it stable. Because of this, it’s important to figure out a way to stabilize the system. More importantly, new control methods will be discovered during the process, and these new methods can be used in many other different systems. The inverted pendulum system can reflect performances such as robustness, mobility and tracking performance. Its dynamic condition is similar to a human walk, and its steady state is similar to the launch system on a rocket’s motion attitude, so the study of the inverted pendulum system is also important to the robot and rocket area. This paper describes the construction of a mathematical model of a first-order inverted pendulum, and the process of designing the fuzzy controller based on the related fuzzy control rules. It also conducts the optimization of the fuzzy controller using a genetic algorithm. After using MATLAB’s Simulink module to simulate the inverted pendulum system and adjust the parameters of the controller, the system could finally reach a stable status within a short period of time, from all kinds of original status, and have anti-jamming performance.
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Abdul Kareem, Ali Fawzi, and Ahmed Abdul Hussein Ali. "Robust Stability Control of Inverted Pendulum Model for Bipedal Walking Robot." Al-Nahrain Journal for Engineering Sciences 23, no. 1 (March 20, 2020): 81–88. http://dx.doi.org/10.29194/njes.23010081.

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This paper proposes robust control for three models of the linear inverted pendulum (one mass linear inverted pendulum model, two masses linear inverted pendulum model and three masses linear inverted pendulum model) which represents the upper, middle and lower body of a bipedal walking robot. The bipedal walking robot is built of light-weight and hard Aluminum sheets with 2 mm thickness. The minimum phase system and non-minimum phase system are studied and investigated for inverted pendulum models. The bipedal walking robot is programmed by Arduino microcontroller UNO. A MATLAB Simulink system is built to embrace the theoretical work. The results showed that one linear inverted pendulum is the worst performance, worst noise rejection and the worst set point tracking to the zero moment point. But two masses linear inverted pendulum models and three masses linear inverted pendulum model have a better performance, a better high-frequency noise rejection characteristic and better set-point tracking to the zero moment point.
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20

Bindu, B., Srikanth N, Haris Raja V, Barath Kumar JK, and Dharmendra R. "Comparative analysis of inverted pendulum control." Scientific Temper 14, no. 02 (June 6, 2023): 516–20. http://dx.doi.org/10.58414/scientifictemper.2023.14.2.44.

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The main motive of this paper is to balance the inverted pendulum system (non-linear model) using controllers and to compare the results obtained from using different controllers. The aim is to determine which controller provides best results with respect to cart’s position and pendulum’s angle. The controllers used in this paper are PI, PD, PID. The inverted pendulum model is modeled using Simscape and the simulation results are obtained using MATLAB
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21

Öksüz, Mehmet, and Recep Halicioğlu. "Alternative Controller Design for Rotary Inverted Pendulum." Tehnički glasnik 12, no. 3 (September 25, 2018): 139–45. http://dx.doi.org/10.31803/tg-20180208152214.

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The inverted pendulum has been considered a classical control problem. Two designs of inverted pendulum are planar and rotary with a nonlinear unstable system characteristic. Inverted pendulum systems are nonlinear. They can be used for testing and studying various observers and controllers. Control of a rotary inverted pendulum is studied here. This paper proposes stabilization of the rotary inverted pendulum at its upright position by using full-state controller. Full-state controllers are designed by using different damping ratios. MATLAB simulation results and the experimental results are taken for 10 degrees step for 5 seconds. The best controller is chosen for SRV02-Rotary inverted pendulum by looking at the simulation and experimental results.
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22

Resti, Nalsa Cintya. "Sifat-Sifat Sistem Pendulum Terbalik dengan Lintasan Berbentuk Lingkaran." INTENSIF 1, no. 1 (February 1, 2017): 20. http://dx.doi.org/10.29407/intensif.v1i1.537.

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The inverted pendulum is a high-order non-linear, miltivariable and highly unstable dynamic system. High-order non-linear systems in the inverted pendulum must be dilutarized to be solved easily. From the calculations that have been done can be deduced that the system from the inverted pendulum is unstable saddle system, can be controlled and can be observed. In addition the system can also be formed into a system of controlled companions and observable forms of kompanion.
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23

Monir, Md. "Analyzing and Designing Control System for an Inverted Pendulum on a Cart." European Scientific Journal, ESJ 14, no. 6 (February 28, 2018): 387. http://dx.doi.org/10.19044/esj.2018.v14n6p387.

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It is a collection of MATLAB functions and scripts, and SIMULINK models, useful for analyzing Inverted Pendulum System and designing Control System for it. Automatic control is a growing field of study in the field of Mechanical Engineering. This covers the proportional, integral and derivative (PID). The principal reason for its popularity is its nonlinear and unstable control. The reports begin with an outline of research into inverted pendulum design system and along with mathematical model formation. This will present introduction and review of the system. Here one dimensional inverted pendulum is analyzed for simulating in MATLAB environment. Control of Inverted Pendulum is a Control Engineering project based on the flight simulation of rocket or missile during the initial stages of flight. The aim of this study is to stabilize the Inverted Pendulum such that the position of the carriage on the track is controlled quickly and accurately so that the pendulum is always erected in its inverted position during such movements.
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Siradjuddin, Indrazno, Zakiyah Amalia, Erfan Rohadi, Budhy Setiawan, Awan Setiawan, Ratna Ika Putri, and Erni Yudaningtyas. "State-feedback control with a full-state estimator for a cart-inverted pendulum system." International Journal of Engineering & Technology 7, no. 4.44 (December 1, 2018): 203. http://dx.doi.org/10.14419/ijet.v7i4.44.26985.

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A Cart Inverted Pendulum System is an unstable, nonlinear and underactuated system. This makes a cart inverted pendulum system used as a benchmark for testing many control method. A cart must occupy the desired position and the angle of the pendulum must be in an equilibrium point. System modeling of a cart inverted pendulum is important for controlling this system, but modeling using assumptions from state-feedback control is not completely valid. To minimize unmeasured state variables, state estimators need to be designed. In this paper, the state estimator is designed to complete the state-feedback control to control the cart inverted pendulum system. The mathematical model of the cart inverted pendulum system is obtained by using the Lagrange equation which is then changed in the state space form. Mathematical models of motors and mechanical transmissions are also included in the cart inverted pendulum system modeling so that it can reduce errors in a real-time application. The state gain control parameter is obtained by selecting the weighting matrix in the Linear Quadratic Regulator (LQR) method, then added with the Leuenberger observer gain that obtained by the pole placement method on the state estimator. Simulation is done to determine the system performance. The simulation results show that the proposed method can stabilize the cart inverted pendulum system on the cart position and the desired pendulum angle.
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Bayram, Atilla, Firat Kara, and Mehmet Nuri Almali. "Design of Spatial Inverted Pendulum System." MATEC Web of Conferences 291 (2019): 02004. http://dx.doi.org/10.1051/matecconf/201929102004.

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Pendulum-based systems which are highly non-linear and unstable have become one of the most widely studied subject of control theory. The close interest of researchers on inverted pendulum problem arises from its strong representation ability with real engineering applications. This study focuses on the design and production of an experimental setup in which a spatial inverted pendulum can be balanced by means of a planar mechanism in RRRRP configuration. A mechanism with two different motion inputs (rotational and linear) that no studies were performed on before was prototyped. This system is highly unstable and shows non-linear dynamic behavior. The mechanical parts that forms the system were manufactured by a 3D printer and a CNC milling machine. At the end of study, a four-degree of freedom spatial inverted pendulum experimental setup has been established on which the control works can be carried out, by installing the electronic and electro-mechanical equipment.
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RAJESH, Tanna, MARY K. ALICE, and VISWANADH VIVEK. "FUZZY CONTROL OF INVERTED PENDULUM SYSTEM." i-manager’s Journal on Instrumentation and Control Engineering 4, no. 2 (2016): 21. http://dx.doi.org/10.26634/jic.4.2.4879.

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27

Long, Hoang Duc, and N. A. Dudarenko. "Analysis of a Cart-Inverted Pendulum System with Harmonic Disturbances Based on its Criterion Matrix." Mekhatronika, Avtomatizatsiya, Upravlenie 23, no. 3 (March 6, 2022): 146–51. http://dx.doi.org/10.17587/mau.23.146-151.

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The control of an inverted pendulum is a classical benchmark control problem. Its dynamics resemble that of many real-world systems of interest like pendulous, missile launchers, segways, and many more. The control of this system is challenging as it is a highly unstable, highly non-linear, non-minimum phase system, and underactuated. Furthermore, the physical constraints on the track position also pose complexity in its control design. A great deal of nonlinearity is present inherently and as well as affected by the surrounding external disturbances. The paper presents an approach for analysis of a cart-inverted pendulum system with harmonic disturbances. The approach is based on the index of the criterion matrix of the system named a degeneration factor. The degeneration factor is constructed with the singular values of the criterion matrix of the system and allows us to find frequency range, where the system operates as a whole. A linear-quadratic regulator is used to control the cart-inverted pendulum system. The results are supported with an example.
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28

Li, Ai Lian, Hong Yu Qi, and Li Liang. "Based on T-S Fuzzy Classification of the Double Inverted Pendulum Multi Mode Adaptive Control." Advanced Materials Research 902 (February 2014): 300–305. http://dx.doi.org/10.4028/www.scientific.net/amr.902.300.

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Double Inverted pendulum as an important object of study on robotics and aviation field, is also a major platform for teaching and scientific research.Usually double Inverted pendulum modeling is usually will be linearized processing system, ignoring the effect of the angle of system. But the realization of double inverted pendulum is a nonlinear system, the angle affect the stability control. From the actual situation of double Inverted pendulum motion, double Inverted pendulum system of the input space is divided into 9 sub-space, by T-S fuzzy and feedback gain matrix to select the corresponding state equation, making the system more close to its dynamic performance. The multi mode adaptive control and T-S fuzzy method of combining the successful implementation of double inverted pendulum system simulation and real-time control.The number of rules they use far less than Mamdani fuzzy, but also successfully resolved the fuzzy control algorithm due to the presence of multiple variables and the resulting "rule explosion problem".
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Zhai, Xiao Hua, Shu Xia Yao, and Zhi Hui Xu. "Research on Fuzzy Control of Inverted Pendulum in the MATLAB Environment." Applied Mechanics and Materials 182-183 (June 2012): 1211–14. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1211.

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Inverted Pendulum is a typical system with multivariate, nonlinear system. Research on inverted pendulum can be attributed to research on nonlinear multivariate absolutely unstable system. Its control methods and ideas have an extensive usage. In this paper, a fuzzy controller is introduced to control single inverted pendulum system, and the performance characteristic of this system is also introduced. The control result of the inverted pendulum is good, the oscillation is small. Research result indicated that the control performance of fuzzy control is to select good membership function and discourse domain.
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30

Tin, Phu Tran, Tran Hoang Quang Minh, Tran Thanh Trang, and Nguyen Quang Dung. "Using real interpolation method for adaptive identification of nonlinear inverted pendulum system." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (April 1, 2019): 1078. http://dx.doi.org/10.11591/ijece.v9i2.pp1078-1089.

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<p>In this paper, we investigate the inverted pendulum system by using real interpolation method (RIM) algorithm. In the first stage, the mathematical model of the inverted pendulum system and the RIM algorithm are presented. After that, the identification of the inverted pendulum system by using the RIM algorithm is proposed. Finally, the comparison of the linear analytical model, RIM model, and nonlinear model is carried out. From the results, it is found that the inverted pendulum system by using RIM algorithm has simplicity, low computer source requirement, high accuracy and adaptiveness in the advantages.</p>
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31

Bradshaw, Alan, and Jindi Shao. "Swing-up control of inverted pendulum systems." Robotica 14, no. 4 (July 1996): 397–405. http://dx.doi.org/10.1017/s0263574700019792.

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SUMMARYIn Part I a technique for the swing-up control of single inverted pendulum system is presented. The requirement is to swing-up a carriage mounted pendulum system from its natural pendent position to its inverted position. It works for all carriage balancing single inverted pendulum systems as the swing-up control algorithm does not require knowledge of the system parameters. Comparison with previous swing-up controls shows that the proposed swing-up control is simpler, eaiser. more efficient, and more robust.In Part II the technique is extended to the case of the swing-up control of double inverted pendulum systems. Use is made of a novel selective partial-state feedback control law. The nonlinear, open-loop unstable, nonminimum-phase. and interactive MIMO pendulum system is actively linearised and decoupled about a neutrally stable equilibrium by the partial-state feedback control. This technique for swing-up control is not at all sensitive to uncertainties such as modelling error and sensor noise, and is both reliable and robust.
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32

Jin, Yu Qiang, Jun Wei Lei, and Di Liu. "Modeling and PID Control of Single-Stage Inverted Pendulum System." Applied Mechanics and Materials 644-650 (September 2014): 142–45. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.142.

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The dynamic model is obtained based on researching the structure of single inverted pendulum system in this paper. Mathematical model of inverted pendulum that is close to the working point is deduced by linearization. A PID control algorithm is put forward by analyzing the factor of influencing inverted pendulum stability. The effectiveness of proposed algorithm is verified by simulation. This algorithm has the features of high control precision and good stability.
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33

Wu, Shuo Mei, Jian Wei Song, and Wen Qing Zhang. "Optimal Control Theory Research on Inverted Pendulum System." Applied Mechanics and Materials 494-495 (February 2014): 1118–21. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1118.

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The state space expression can be deduced by establishing the mathematical model of inverted pendulum system. In this paper, linear quadratic regulator (LQR) is used to control the inverted pendulum system, providing better balance between system robustness stability and rapidity. The simulation structure shows that the better the system anti-interference capability is, the shorter its recovery time is. Good control effect can be achieved by applying linear quadratic optimal control in the control of double inverted pendulum balancing system.
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34

Maneetham, Dechrit, and Petrus Sutyasadi. "System design for inverted pendulum using LQR control via IoT." International Journal for Simulation and Multidisciplinary Design Optimization 11 (2020): 12. http://dx.doi.org/10.1051/smdo/2020007.

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This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.
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35

Sun, Jian Zhong, Jian Kang Lu, Bin Yang, and Jun Li Li. "Sliding Mode Variable Structural Control of Nonlinear Inverted Pendulum." Advanced Materials Research 433-440 (January 2012): 74–80. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.74.

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In this paper, the multi-input linear and nonlinear mathematical differential equations of inverted pendulum system were established based on the traditional single-input linear inverted pendulum. Aiming at multi-input nonlinear model, nonlinear state transformation are carried through on the basis of the test of distribution involution and the calculation of integral manifold, then, the multi-input nonlinear inverted pendulum system was transformed into two single-input nonlinear inverted pendulum system to study. In the end, make use of related nonlinear system control theory of the sliding mode variable structure, designed the controller structure.
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36

Sanjeewa, Sondarangallage DA, and Manukid Parnichkun. "Control of rotary double inverted pendulum system using mixed sensitivity H∞ controller." International Journal of Advanced Robotic Systems 16, no. 2 (March 1, 2019): 172988141983327. http://dx.doi.org/10.1177/1729881419833273.

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Balancing control of a rotary double inverted pendulum system is a challenging research topic for researchers in dynamics control field because of its nonlinear, high degree-of-freedom, under actuated and unstable characteristics. The system always works under uncertainties and disturbances. Many control algorithms fail or ineffectively control the rotary double inverted pendulum system. In this article, mixed sensitivity H∞ control is proposed to balance the rotary double inverted pendulum system. The controller is proposed to ensure the robust stability and enhance the time domain performance of the system under uncertainties and disturbances. Structure of the system, dynamics model and controller synthesis are presented. For performance evaluation, the proposed mixed sensitivity H∞ controller is compared with linear quadratic regulator from both simulation and experiment on the rotary double inverted pendulum system. The results show high performance of the proposed controller on the rotary double inverted pendulum system with model uncertainties and external disturbances.
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37

Sen, Muhammed Arif, and Mete Kalyoncu. "Optimisation of a PID Controller for an Inverted Pendulum Using the Bees Algorithm." Applied Mechanics and Materials 789-790 (September 2015): 1039–44. http://dx.doi.org/10.4028/www.scientific.net/amm.789-790.1039.

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The inverted pendulum system is a challenging control problem in the control theory, which continually moves away from a stable state. The paper presents the design of a Proportional-Integral-Derivative (PID) controller for a single-input multi-output (SIMO) inverted pendulum system and using the Bees Algorithm (BA) to obtain optimal gains for PID controllers. The Bees Algorithm optimizes the gains so that the controller can move the cart to a desired position with the minimum amount of the change in the pendulum’s angle from the vertically upright position during the movement. The tuning aim is to minimize the control responses of the cart’s position and the pendulum’s angle in time domain. MATLAB/Simulink simulation has been performed to demonstrate that the effects on the system performance of PID controllers with optimal gains. The obtained results show that the tuning method by using the Bees Algorithm produced PID controllers successfully within the controller design criteria. Following a description of the inverted pendulum system and the Bees Algorithm, the paper gives the obtained simulation results for the system demonstrating the efficiency of the design.
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38

Rahmawaty, Made. "Modeling, Simulation, and Stabilization of Two Wheels Inverted Pendulum Robot Using Hybrid Fuzzy Control." Indonesian Journal of electronics, electromedical engineering, and medical informatics 3, no. 3 (August 27, 2021): 93–98. http://dx.doi.org/10.35882/ijeeemi.v3i3.2.

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Two wheels inverted pendulum robot has the same characteristics as inverted pendulum, which are unstable and nonlinear. Nonlinear systems can often be linearized by approximating them by a linear system obtained by expanding the nonlinear solution in a series, and then linear techniques can be used. Fuzzy logic control is the famous nonlinear controller that has been used by researchers to analyze the performance of a system due to the easiness to understand the nature of the controller. This research discusses about two wheels inverted pendulum robot design using hybrid fuzzy control. There are two types of fuzzy control, namely Fuzzy Balanced Standing Control (FBSC) to maintain stability and Fuzzy Traveling and Position Control (FTPC) to maintain position. Based on Takagi-Sugeno (T-S) fuzzy model on two wheels inverted pendulum robot, FBSC control used Parallel Distributed Compensation (PDC) with pole placement technic. Based on two wheels inverted pendulum robot movement characteristics, FTPC was designed using Mamdani Fuzzy architecture. FTPC control is used to help FBSC to maintain robot stability and to adjust to the desired position. Simulation result shows that controller for two wheels inverted pendulum robot can stabilize pendulum angle in 0 radian and close to the desired position
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39

Qi, Shu Fen, Huan Huan Liu, and Hong Tao Tian. "Research of the Inverted Pendulum System Based on the Linear Quadratic Optimal Control." Applied Mechanics and Materials 568-570 (June 2014): 1104–7. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1104.

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As an ideal experimental method in the study of control theory, inverted pendulum system is an indispensable tool to examine the effects of control strategy. In this paper the corresponding mathematical model and the state space equation are established according to studying the working principle and balance control problem of the single stage linear inverted pendulum system. Using MATLAB solves them and gets the consequences. Finally, the linear quadratic optimal control strategy is used to design the controller of single-stage inverted pendulum system, and a simulation study is carried out. The simulation results show the effectiveness of the most sorrow regulator of the quadratic. And basic rule can be found out between the dynamic response of the inverted pendulum system and weighting matricesandin the LQR.
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40

Shi, Xiang, Zhe Xu, Ka Tian, and Qing Yi He. "Optimal Control for Wheeled Inverted Pendulum Based on Collaborative Simulation." Applied Mechanics and Materials 556-562 (May 2014): 2444–47. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2444.

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To control wheeled inverted pendulum is a good way to test all kinds of theories of control. The optimal control based on MATLAB is used to control wheeled inverted pendulum, and the control law is designed, and its feasibility is verified. However the mathematical model of the wheeled inverted pendulum is linearized and inverted pendulum is a high-order nonlinear system, both of them exist errors. Then the collaborative simulation of MATLAB and ADAMS is also used to control wheeled inverted pendulum, in which wheeled inverted pendulum is built up to virtual prototype model in ADAMS based on virtual prototype technology, and the control law designed from simulation of MATLAB is consulted. At last the results of simulation demonstrate the correctness of optimal control of wheeled inverted pendulum, and it also indicates the way is worth advocating in the study.
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41

Elkinany, Boutaina, Mohammed Alfidi, Redouane Chaibi, and Zakaria Chalh. "T-S Fuzzy System Controller for Stabilizing the Double Inverted Pendulum." Advances in Fuzzy Systems 2020 (December 5, 2020): 1–9. http://dx.doi.org/10.1155/2020/8835511.

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This article provides a representation of the double inverted pendulum system that is shaped and regulated in response to torque application at the top rather than the bottom of the pendulum, given that most researchers have controlled the double inverted pendulum based on the lower part or the base. To achieve this objective, we designed a dynamic Lagrangian conceptualization of the double inverted pendulum and a state feedback representation based on the simple convex polytypic transformation. Finally, we used the fuzzy state feedback approach to linearize the mathematical nonlinear model and to develop a fuzzy controller H ∞ , given its great ability to simplify nonlinear systems in order to reduce the error rate and to increase precision. In our virtual conceptualization of the inverted pendulum, we used MATLAB software to simulate the movement of the system before applying a command on the upper part of the system to check its stability. Concerning the nonlinearities of the system, we have found a state feedback fuzzy control approach. Overall, the simulation results have shown that the fuzzy state feedback model is very efficient and flexible as it can be modified in different positions.
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42

Bajrami, Xhevahir, Arbnor Pajaziti, Ramë Likaj, Ahmet Shala, Rinor Berisha, and Mirlind Bruqi. "Control Theory Application for Swing Up and Stabilisation of Rotating Inverted Pendulum." Symmetry 13, no. 8 (August 13, 2021): 1491. http://dx.doi.org/10.3390/sym13081491.

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This paper introduces a new scheme for sliding mode control using symmetry principles for a rotating inverted pendulum, with the possibility of extension of this control scheme to other dynamic systems. This was proven for swing up and stabilisation control problems via the new sliding mode control scheme using both simulations and experiments of rotary inverted pendulum (RIP) underactuated systems. According to the Lyapunov theory, a section of the pendulum was compensated with a scale error in the upright position, as the desired trajectory was followed by the pendulum arm section. As the RIP’s dynamic equations were nonlinearly complex and coupled, the complex internal dynamics made the task of controller design difficult. The system control for the pathway of the reference model of the rotational actuator with the application of the sliding mode technique for moving back and forth up the inverted pendulum’s structure, till the arm to reach the linear range round the vertical upright position, was created and tested in an existent device. The stabilisation scheme was switched on in the sliding mode as soon as the arm reached the linear range. A comparison of the stabilisation performance for the same rotating inverted pendulum as discussed by other authors revealed that the proposed controller was more flexible and reliable in terms of the swing up and stabilisation time.
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43

Kumagai, Masaaki, and Takaya Ochiai. "Development of a Robot Balanced on a Ball - First Report, Implementation of the Robot and Basic Control -." Journal of Robotics and Mechatronics 22, no. 3 (June 20, 2010): 348–55. http://dx.doi.org/10.20965/jrm.2010.p0348.

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This paper proposes the implementation and control scheme of a robot balanced on a ball. Unlike a twowheeled inverted pendulum, such as the Segway Human Transporter, an inverted pendulum using a ball moves in any direction without changing orientation, enabling isotropic movement and stabilization. The robot on the ball can be used in place of the twowheeled robots. Our robot has three omnidirectional wheels with stepping motors that drive the ball and two sets of rate gyroscopes and accelerometers as attitude sensors. It can keep station, traverse in any direction, and turn around its vertical axis. Inverted pendulum control is applied to two axes to maintain attitude. Ball acceleration is used as control input of the system, unlike most of inverted pendulums which use torque or force as input. This acceleration input makes the robot robust against change of inertia parameters, as confirmed by Nyquist diagrams. The mechanism of the robot, the control method, and the experimental results are described in this paper.
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44

Wang, Li Qian, and Kai Hu. "Control System Design of Rotary Inverted Pendulum." Applied Mechanics and Materials 608-609 (October 2014): 766–69. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.766.

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In this paper we study the control system of single stage rotary inverted pendulum, and put forwards the controller design based on the core of STM32. In control strategy we use the classical control theory-PID control algorithm, which realizes the closed-loop control of rotating arm and swing rod for the single stage rotary inverted pendulum. The final test results show that the control strategy is effective.
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45

Popławski, Krzysztof, Leszek Ambroziak, and Mirosław Kondratiuk. "Electro Pneumatic Control System for Inverted Pendulum." Acta Mechanica et Automatica 14, no. 2 (June 1, 2020): 91–97. http://dx.doi.org/10.2478/ama-2020-0013.

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AbstractThe paper concerns the inverted pendulum control system with using pneumatic cylinder. A mathematical model of the pendulum used to derive the LQG controller was presented. Prepared laboratory stand was presented and described in detail. The main purpose of the work was experimental researches. A number of control process tests were conducted with variable model parameters such as additional mass, injected disturbances and so on. The results were shown on the time plots of the control object states.
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46

Hua, Yang, and Zi Jian Yang. "Simple Rotary Inverted Pendulum and the Control Device." Applied Mechanics and Materials 851 (August 2016): 445–48. http://dx.doi.org/10.4028/www.scientific.net/amm.851.445.

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Inverted pendulum control system is a complex, nonlinear, unstable system. This design on the basis of studying the law of motion of the inverted pendulum, build its trajectory mathematical model, using MATLAB simulation analysis, after understanding of inverted pendulum model, use k60 micro controller combined with PID algorithm gives the signal driven dc gear motor, and then to control the inverted pendulum system, used in the process of standing on your head swinging rod Angle encoder acquisition, processing, the Angle of swinging rod feedback on point of view, the direction of the angular velocity, the motor running direction, adjusting handstand pendulum rod by using PD algorithm, PI parameters to adjust motor speed, by double circuit PD/PI control scheme realizes the rotating arm swinging rod Angle and position closed loop control at the same time.
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47

Fajar, M., S. S. Douglas, and J. B. Gomm. "Modelling and Simulation of Spherical Inverted Pendulum Based on LQR Control with SimMechanics." Applied Mechanics and Materials 391 (September 2013): 163–67. http://dx.doi.org/10.4028/www.scientific.net/amm.391.163.

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This paper describes how to simulate the spherical inverted pendulum, a dynamics of multibody system, with SimMechanics. The control strategy used is based on the LQR feedback method for the stabilisation of the spherical inverted pendulum system. Simulation study has been done in Simulink environment shows that LQR controller is capable to control multi input and multi output of spherical inverted pendulum system successfully. The result shows that LQR control strategy gives satisfactory response that is presented in time domain with the details analysis. The use of SimMechanics for simulation of spherical inverted pendulum has some advantages i.e. not need to derive equations of motion, available visualisation tools, fast and easy design
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48

Thanoon, Mohammad A., Sohaib R. Awad, and Ismael Kh Abdullah. "LQR controller design for stabilization of non-linear DIP system based on ABC algorithm." Eastern-European Journal of Enterprise Technologies 2, no. 2 (122) (April 17, 2023): 36–44. http://dx.doi.org/10.15587/1729-4061.2023.275657.

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Inverted pendulum systems, such as double or single, rotational or translational inverted pendulums are non-linear and unstable, which have been the most dominant approaches for control systems. The double inverted pendulum is one kind of a non-linear, unstable system, multivariable, and strong coupling with a wide range of control methods. To model these types of systems, many techniques have been proposed so that motivating researchers to come up with new innovative solutions. The Linear Quadratic Regulator (LQR) controller has been a common controller used in this field. Meanwhile, the Artificial Bee Colony (ABC) technique has become an alternative solution for employing Bee Swarm Intelligence algorithms. The research solutions of the artificial bee colony algorithm in the literature can be beneficial, however, the utilization of discovered sources of food is ineffective. Thus, in this paper, we aim to provide a double inverted pendulum system for stabilization by selecting linear quadratic regulator parameters using a bio-inspired optimization methodology of artificial bee colony and weight matrices Q and R. The results show that when the artificial bee colony algorithm is applied to a linear quadratic regulator controller, it gains the capacity to autonomously tune itself in an online process. To further demonstrate the efficiency and viability of the suggested methodology, simulations have been performed and compared to conventional linear quadratic regulator controllers. The obtained results demonstrate that employing artificial intelligence (AI) together with the proposed controller outperforms the conventional linear quadratic regulator controllers by more than 50 % in transient response and improved time response and stability performance
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49

Cao, Rong Min, Hui Xing Zhou, and Rong Hua Ma. "Experiment Platform Design cSPACE-Based for a Permanent Magnet Linear Synchronous Motor Driven Inverted Pendulum." Applied Mechanics and Materials 84-85 (August 2011): 452–56. http://dx.doi.org/10.4028/www.scientific.net/amm.84-85.452.

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Permanent magnet linear synchronous motor (PMLSM) driven inverted pendulum is a new member of present similar devices, various unexpected disturbances such as lag effect of a belt attached to a cart and errors caused by a rotary encoder while detecting the position of a cart can be eliminated or reduced to a small range.In this paper, ironless permanent magnet synchronous linear motor driven inverted pendulum experiment platform is developed. The plant is hardware in the loop real time simulation control development system (Hardware-in-Loop, HIL)based on TMS320F2812DSP and MATLAB, it can use simple and efficient way to achieve linear motor driven inverted pendulum real-time control. Long design time for programming and debugging difficulty are avoided for traditional programming language. Control algorithm can be investigated directly on MATLAB/Simulink, and can be generated automatically control code to control single and double -stage inverted pendulum system. The real performance of the driven inverted pendulum is researched in this paper, the results showed that the controllability of the driven inverted pendulum is fine.
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50

Nguyen, Chiem, Hai Phan, and Hung Nguyen. "An energy saving method of stable control of inverted pendulum system when affected by external interference using auxiliary pendulum." E3S Web of Conferences 104 (2019): 01015. http://dx.doi.org/10.1051/e3sconf/201910401015.

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This research aims to develop a method to reduce energy consumption when controlling an inverted pendulum system that is affected by external interference. In this paper, the authors use the quasi time-optimal control law and add on an inverted pendulum an auxiliary pendulum to absorb the energy of the external interference effects, to reduce the cost of controlling the energy stable inverted pendulum while ensuring system quality. The quality of the method is demonstrated through simulation results. The effectiveness of this method is shown by comparison with the method of no damping.
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