Development of Teaching Materials for Learning the Linear Control Theory with an Inverted Pendulum System

2004 ◽  
Vol 2004 (0) ◽  
pp. 120
Author(s):  
R Hayakawa ◽  
H Hayashi ◽  
R Kawatani
Keyword(s):  
Control Theory ◽  
Inverted Pendulum ◽  
Linear Control ◽  
Teaching Materials ◽  
Pendulum System ◽  
Linear Control Theory ◽  
Inverted Pendulum System

Adaptive Neural Network Fuzzy Control Plane Double Inverted Pendulum

2013 ◽  
Vol 765-767 ◽  
pp. 2004-2007
Author(s):  
Su Ying Zhang ◽  
Ying Wang ◽  
Jie Liu ◽  
Xiao Xue Zhao
Keyword(s):  
Neural Network ◽  
Fuzzy Control ◽  
Control Theory ◽  
Inverted Pendulum ◽  
Learning Ability ◽  
Adaptive Neural Network ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Self Learning ◽  
Controlled Object

Double inverted pendulum system is nonlinear and unstable. Fuzzy control uses some expert's experience knowledge and learns approximate reasoning algorithm. For it does not depend on the mathematical model of controlled object, it has been widely used for years. In practical engineering applications, most systems are nonlinear time-varying parameter systems. As the fuzzy control theory lacks of on-line self-learning and adaptive ability, it can not control the controlled object effectively. In order to compensate for these defects, it introduced adaptive, self-organizing, self-learning functions of neural network algorithm. We called it adaptive neural network fuzzy inference system (ANFIS). ANFIS not only takes advantage of the fuzzy control theory of abstract ability, the nonlinear processing ability, but also makes use of the autonomous learning ability of neural network, the arbitrary function approximation ability. The controller was applied to double inverted pendulum system and the simulation results showed that this method can effectively control the double inverted pendulum system.

scholarly journals Linear Quadratic Gaussian Regulator for the Nonlinear Observer-Based Control of a Dynamic Base Inverted Pendulum

2021 ◽  
Vol 13 (3) ◽  
pp. 79-90
Author(s):  
K. Z. MIRZA
Keyword(s):  
Inverted Pendulum ◽  
Control Mechanism ◽  
Linear Quadratic Regulator ◽  
Nonlinear Observer ◽  
Linear Control ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
The Given

The inverted pendulum is a non-linear control problem permanently tending towards instability. The main aim of this study is to design a controller capable enough to work within the given conditions while also keeping the pendulum erect given the impulsive movement of the cart to which it is joint via a hinge. The first half of the paper presents the mathematical modelling of the dynamic system, together with the design of a linear quadratic regulator (LQR). This paper also discusses a novel adaptive control mechanism employing a Kalman filter for the mobile inverted pendulum system (MIPS). In the second half of the paper, a Gaussian Quadratic Linear Controller (LQG) is adapted to improve on previous deficiencies. The simulation is done through Simulink and results show that both controllers are capable of managing the multiple output model. However, data from simulations clearly showed that an LQG controller is a better choice.

Predictor-network-based MRACS for inverted pendulum system.

1991 ◽  
Vol 111 (3) ◽  
pp. 221-229 ◽  
Author(s):  
Motomiki Uchida ◽  
Yukihiro Toyoda ◽  
Yoshikuni Akiyama ◽  
Kazushi Nakano ◽  
Hideo Nakamura
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System

Optimal PID Design Approaches for an Inverted Pendulum System

2016 ◽  
Vol 9 (3) ◽  
pp. 167 ◽  
Author(s):  
Muhammad Sani Gaya ◽  
Anas Abubakar Bisu ◽  
Syed Najib Syed Salim ◽  
I. S. Madugu ◽  
L. A. Yusuf ◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Pendulum System ◽  
Inverted Pendulum System
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