Application of GA to design LQR controller for an Inverted Pendulum System

2009 ◽  
Author(s):  
C. Wongsathan ◽  
C. Sirima
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller

scholarly journals Multibody Modeling and Balance Control of a Reaction Wheel Inverted Pendulum Using LQR Controller

2021 ◽  
Vol 1 (1) ◽  
pp. 84-89
Author(s):  
Ümit Önen ◽  
Abdullah Çakan
Keyword(s):  
State Space ◽  
Inverted Pendulum ◽  
Balance Control ◽  
Space Representation ◽  
Reaction Wheel ◽  
Linear Quadratic ◽  
Pendulum System ◽  
State Space Representation ◽  
Inverted Pendulum System ◽  
Lqr Controller

In this study, modeling and LQR control of a reaction wheel inverted pendulum system is described. The reaction wheel inverted pendulum model is created by using a 3D CAD platform and exported to Simscape Multibody. The multibody model is linearized to derive a state-space representation. A LQR (Linear-quadratic regulator) controller is designed and applied for balance control of the pendulum. The results show that deriving a state-space representation from multibody is an easy and effective way to model dynamic systems and balance control of the reaction wheel inverted pendulum is successfully achieved by LQR controller. Results are given in the form of graphics.

scholarly journals USING GENETIC ALGORITHM IN OPTIMIZING THE MATRIX OF LQR CONTROLLER FOR NONLINEAR INVERTED PENDULUM SYSTEM

2019 ◽  
Vol 1 (28) ◽  
pp. 50-55
Author(s):  
Tan Thanh Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Pendulum Model ◽  
The Matrix ◽  
Lqr Controller ◽  
Genetic Algorithm Method

In this article, the author used the matlab software to simulate and then compared the results between the classical LQR (Linear Quadratic Regulator) controller and another method to adjust the matrix parameters toward optimization of the LQR controller. It is the GA (Genetic Algorithm) method to optimize the matrix of the LQR controller, and the results have  been verified on the nonlinear pendulum model. The Genetic Algorithm is a modern control algorithm, which is widely applied in research and practice. The main objective of this article is to use the GA algorithm in order to optimize the matrix parameters of LQR controller, whichcontrolled the position and angle of the nonlinear inverted pendulum at the stable balance point. The matlab-based simulating results showed that  the system has operated properly to the requirements and the output response has reached an equilibrium position of about 2.5 seconds.

MBPOA-based LQR controller and its application to the double-parallel inverted pendulum system

2014 ◽  
Vol 36 ◽  
pp. 262-268 ◽  
Author(s):  
Ling Wang ◽  
Haoqi Ni ◽  
Weifeng Zhou ◽  
Panos M. Pardalos ◽  
Jiating Fang ◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller

Design and Performance Analysis of LQR Controller for Stabilizing Double Inverted Pendulum System

2017 ◽  
Vol 2 (9) ◽  
pp. 1-5
Author(s):  
Ghassan A. Sultan ◽  
Ziyad K. Farej
Keyword(s):  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Pendulum System ◽  
Inverted Pendulum Model ◽  
Inverted Pendulum System ◽  
Pendulum Model ◽  
Lqr Controller ◽  
And Performance ◽  
Performance Results

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.

Optimal Design of LQR Controller Based on Improved Artificial Bee Colony Optimization Algorithm

2014 ◽  
Vol 971-973 ◽  
pp. 1272-1275 ◽  
Author(s):  
Huai De Yang
Keyword(s):  
Artificial Bee Colony ◽  
Inverted Pendulum ◽  
Balance Control ◽  
Pendulum System ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Bee Colony Optimization ◽  
The Mathematical Model

The inverted pendulum system is characterized as a typical nonlinear, fast multi-variable, essentially unstable system. It is difficult to control because of its instability .In order to improve balance control, the mathematical model of the single inverted pendulum is established, a LQR controller is designed which is based on improved artificial bee colony. Experiments show that the improved algorithm has better performance than standard artificial bee colony algorithm on convergence and rate balance control to meet the requirements of the single inverted pendulum.

Modelling and Simulation of Spherical Inverted Pendulum Based on LQR Control with SimMechanics

2013 ◽  
Vol 391 ◽  
pp. 163-167 ◽  
Author(s):  
M. Fajar ◽  
S.S. Douglas ◽  
J.B. Gomm
Keyword(s):  
Time Domain ◽  
Control Strategy ◽  
Inverted Pendulum ◽  
Multibody System ◽  
Equations Of Motion ◽  
Pendulum System ◽  
Lqr Control ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Feedback Method

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

Robust Controller Design for Inverted Pendulum System

2013 ◽  
Vol 631-632 ◽  
pp. 1342-1347
Author(s):  
Xu Cao ◽  
Nian Feng Li ◽  
Hua Xun Zhang
Keyword(s):  
Inverted Pendulum ◽  
Controller Design ◽  
Robust Controller ◽  
Important Indicator ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Coupling Characteristics ◽  
The Stability ◽  
Robust Controller Design

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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