The modelling and control of flywheel inverted pendulum system

2010 ◽  
Author(s):  
Xiao-gang Ruan ◽  
Yu-feng Wang
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
And Control

scholarly journals Integrated SolidWorks and Simscape platform for the design and control of an inverted pendulum system

2020 ◽  
Vol 71 (2) ◽  
pp. 122-126
Author(s):  
Ahmed Alkamachi
Keyword(s):  
Inverted Pendulum ◽  
Controller Design ◽  
State Feedback Control ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Control Scheme ◽  
Implicit System ◽  
Physical Elements ◽  
And Control ◽  
The Mathematical Model

AbstractA single inverted pendulum on a cart (SIPC) is designed and modeled physically using SolidWorks. The model is then exported to the Simulink environment to form a Simscape model for simulation and test purposes. This type of modeling uses a physical grid tactic to model mechanical structures. It requires connection of the physical elements with physical signal converter to define the implicit system dynamics to be modeled. The integration between the SolidWorks and Simscape eliminates the need of deriving the mathematical model and provides a platform for the rapid controller design for the system. State feedback control scheme is proposed, designed, and tuned aiming to maintain the pendulum in the upright place while tracking the desired cart position. Several simulation cases are studied to prove the controller abilities. In order to examine the controller robustness, disturbance rejection and noise attenuation capabilities are also discovered.

DESIGN AND CONTROL OF A FLYWHEEL INVERTED PENDULUM SYSTEM

2018 ◽  
Author(s):  
José Roberto Canuto Vasconcelos ◽  
Elizabeth Maria Astorga González ◽  
Pedro Manuel González del Foyo
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
And Control

2A2-A06 Angle Control of Inverted Pendulum System by Brake Control(Mechanism and Control for Actuator(2))

2012 ◽  
Vol 2012 (0) ◽  
pp. _2A2-A06_1-_2A2-A06_4
Author(s):  
Ryutaro OCHIAI ◽  
Ryohei YAMATE ◽  
Yasuhiro MINAMIYAMA ◽  
Takanori KIYOTA ◽  
Noboru SUGIMOTO
Keyword(s):  
Inverted Pendulum ◽  
Control Mechanism ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
And Control

scholarly journals Development of Graphical Interface System for Inverted Pendulum Stabilization

2019 ◽  
pp. 150
Author(s):  
Erwin Susanto
Keyword(s):  
Inverted Pendulum ◽  
Control Design ◽  
Mathematic Model ◽  
Graphical Interface ◽  
Control Engineering ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Interface System ◽  
The Stability ◽  
And Control

Currently, most of basic control engineering lectures teach both mathematic model and control of an inverted pendulum to explain stability problems in dynamic systems. The inverted pendulum system is a pendulum controlled with a certain force in order to stand in balance around vertical equilibrium line. Hence this system is a highly unstable system and needs stabilization methods using a  kind of controller. This paper describes how to design a Proportional Derivative Integral (PID) controller via root locus technique to stabilize it and realization of its interface system for monitoring angle trajectory. This visualization is needed to observe the stability and  effectiveness of its mathematic model and control design. Experimental results and analysis show that control design and interface system can be implemented well.

Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers

2017 ◽  
Vol 6 (4) ◽  
pp. 21-32
Author(s):  
Ashwani Kharola ◽  
Pravin P. Patil
Keyword(s):  
Inverted Pendulum ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Transverse Displacement ◽  
Inference System ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Highly Nonlinear ◽  
Training Error ◽  
And Control

Elastic Inverted Pendulum system (EIP) are very popular objects of theoretical investigation and experimentation in field of control engineering. The system becomes highly nonlinear and complex due to transverse displacement of elastic pole or pendulum. This paper presents a comparison study for control of EIP using fuzzy and hybrid adaptive neuro fuzzy inference system (ANFIS) controllers. Initially a fuzzy controller was designed, which was used for training and tuning of ANFIS controller using gbell shape membership functions (MFs). The performance of complete system was evaluated through output responses of settling time, steady state error and maximum overshoot. The study also highlights effect of varying number of MFs on training error of ANFIS. The results showed better performance of ANFIS controller compared to fuzzy controller.

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