scholarly journals Arm Angle Tracking Control with Pole Balancing Using Equivalent Input Disturbance Rejection for a Rotational Inverted Pendulum

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2745
Author(s):  
Hojin Lee ◽  
Jeonghwan Gil ◽  
Sesun You ◽  
Yonghao Gui ◽  
Wonhee Kim
Keyword(s):  
Tracking Control ◽  
Inverted Pendulum ◽  
Lyapunov Theory ◽  
Parameter Uncertainties ◽  
Pass Filter ◽  
Pendulum System ◽  
Low Pass Filter ◽  
Input Disturbance ◽  
Inverted Pendulum System ◽  
Equivalent Input Disturbance

This paper proposes a robust tracking control method for swing-up and stabilization of a rotational inverted pendulum system by applying equivalent input disturbance (EID) rejection. The mathematical model of the system was developed by using a Lagrangian equation. Then, the EID, including external disturbances and parameter uncertainties, was defined; and the EID observer was designed to estimate EID using the state observer dynamics and a low-pass filter. For robustness, the linear-quadratic regulator method is used with EID rejection. The closed-loop stability is proven herein using the Lyapunov theory and input-to-state stability. The performance of the proposed method is validated and verified via experimental results.

H∞ tracking control for an inverted pendulum

2018 ◽  
Vol 24 (16) ◽  
pp. 3515-3524 ◽  
Author(s):  
M Ashok Kumar ◽  
S Kanthalakshmi
Keyword(s):  
Weight Function ◽  
Tracking Control ◽  
Inverted Pendulum ◽  
Weight Functions ◽  
Pendulum System ◽  
Shaping Technique ◽  
Inverted Pendulum System ◽  
Loop Shaping ◽  
Loop Transfer Function ◽  
And Performance

The objective of this paper is to design an [Formula: see text] controller for an inverted pendulum system, synthesized using the [Formula: see text] loop shaping technique. In the [Formula: see text] loop shaping technique, a linear plant model is augmented with certain weight functions, such as the sensitivity weight function and complementary sensitivity weight function, so that the closed loop transfer function of the plant will have the desired performance. In this work, the [Formula: see text] controller is synthesized and the analysis on robustness and performance of the system is done by taking the singular value response and robustness indicator plots.

scholarly journals Heuristic Global Optimization of an Adaptive Fuzzy Controller for the Inverted Pendulum System: Experimental Comparison

2020 ◽  
Vol 10 (18) ◽  
pp. 6158
Author(s):  
Miguel Llama ◽  
Alejandro Flores ◽  
Ramon Garcia-Hernandez ◽  
Victor Santibañez
Keyword(s):  
Real Time ◽  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Parameter Tuning ◽  
Lyapunov Theory ◽  
Experimental Comparison ◽  
Pendulum System ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Inverted Pendulum System

In this paper an adaptive fuzzy controller is proposed to solve the trajectory tracking problem of the inverted pendulum on a cart system. The designed algorithm is featured by not using any knowledge of the dynamic model and incorporating a full-state feedback. The stability of the closed-loop system is proven via the Lyapunov theory, and boundedness of the solutions is guaranteed. The proposed controller is heuristically tuned and its performance is tested via simulation and real-time experimentation. For this reason, a tuning method is investigated via evolutionary algorithms: particle swarm optimization, firefly algorithm and differential evolution in order to optimize the performance and verify which technique produces better results. First, a model-based simulation is carried out to improve the parameter tuning of the fuzzy systems, and then the results are transferred to real-time experiments. The optimization procedure is presented as well as the experimental results, which are also discussed.

scholarly journals Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hongliang Gao ◽  
Xiaoling Li ◽  
Chao Gao ◽  
Jie Wu
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Tracking Control ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Control Method ◽  
Rbf Neural Network ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Tracking Signal

This paper presents several control methods and realizes the stable tracking for the inverted pendulum system. Based on the advantages of RBF and traditional PID, a novel PID controller based on the RBF neural network supervision control method (PID-RBF) is proposed. This method realizes the adaptive adjustment of the stable tracking signal of the system. Furthermore, an improved PID controller based on RBF neural network supervision control strategy (IPID-RBF) is presented. This control strategy adopts the supervision control method of feed-forward and feedback. The response speed of the system is further improved, and the overshoot of the tracking signal is further reduced. The tracking control simulation of the inverted pendulum system under three different signals is given to illustrate the effectiveness of the proposed method.

scholarly journals Trajectory Azimuth Control Based on Equivalent Input Disturbance Approach for Directional Drilling Process

2021 ◽  
Vol 25 (1) ◽  
pp. 31-39
Author(s):  
Zhen Cai ◽  
Xuzhi Lai ◽  
Min Wu ◽  
Chengda Lu ◽  
Luefeng Chen ◽  
...  
Keyword(s):  
State Space Model ◽  
System Stability ◽  
Linear Matrix ◽  
Drilling Process ◽  
Drill Bit ◽  
Directional Drilling ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Input Disturbance ◽  
Equivalent Input Disturbance

This paper concerns with trajectory azimuth control in directional drilling. The motion process of the drill bit and a series of stabilizers are described, and a state-space model of the trajectory azimuth is constructed. The scheme of the trajectory azimuth control system is designed based on the equivalent input disturbance approach. An internal model is inserted to track the drill bit to improve the quality of the drilling trajectory. A state observer is combined with a low-pass filter to estimate the trajectory azimuth by measuring the azimuth of the bottom hole assembly (BHA). The control parameters can be obtained by the condition of system stability, which is derived in terms of linear matrix inequalities. A typical case is used to illustrate the validity and robustness of our approach.

Oscillatory Tracking Control of a Class of Nonlinear Systems

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Zheng Wang ◽  
Yi Guo
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
State Feedback ◽  
Inverted Pendulum ◽  
Feedforward Control ◽  
Initial Conditions ◽  
Pendulum System ◽  
Physical Systems ◽  
Inverted Pendulum System ◽  
State Measurement

Vibration control is an effective alternative to conventional feedback and feedforward control. Motivated by its important application in physical systems and few results on general oscillatory tracking control, we consider tracking control of a class of nonlinear systems using oscillation in the paper. We propose a new oscillatory control design using general averaging analysis for the tracking problem. Based on the oscillation functions associated with accessible vibrating components of the system, oscillatory control is designed to track a desired trajectory. Comparing to existing oscillatory tracking control, our approach is robust to initial conditions. We show the effectiveness of the proposed method by two simulation examples, which include a second-order nonholonomic integrator and the inverted pendulum system. For the inverted pendulum system, we show that our designed oscillatory control does not need state feedback to track a desired trajectory, which is desirable for systems where state measurement is not feasible.

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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