Stabilizing x -z Inverted Pendulum via Fractional Order PID Controller

2020 ◽  
Author(s):  
Satyendra Kumar ◽  
Moina Ajmeri
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

scholarly journals A performance analysis of fractional order based MARC controller over optimal fractional order PID controller on inverted pendulum

2018 ◽  
Vol 7 (2.21) ◽  
pp. 29
Author(s):  
Deep Mukherjee ◽  
Palash Kumar Kundu ◽  
Apurba Ghosh
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Dynamic Performance ◽  
Performance Criteria ◽  
Advanced Technique ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

This paper presents a new way to design MIT rule as an advanced technique of MARC (Model Adaptive Reference Controller) for an integer order inverted pendulum system. Here, our work aims to study the performance characteristics of fractional order MIT rule of MARC controller followed by optimal fractional order PID controller in MATLAB SIMULINK environment with respect to time domain specifications. Here, to design fractional order MIT rule Grunwald-Letnikov fractional derivative calculus method has been considered and based on Grunwald-Letnikov fractional calculus rule fractional MIT rule has been designed in SIMULINK. The proposed method aims finally to analyze overall desired closed loop dynamic performance on inverted pendulum with different performance criteria and to show the desired nature of an unstable system over optimal fractional order PID controller. 

A Better Stability Control of Inverted Pendulum System Using FMINCON Based FOPID Controller Over Fractional Order Based MRAC Controller

2019 ◽  
Vol 8 (1) ◽  
pp. 18-30
Author(s):  
Deep Mukherjee ◽  
Palash Kundu ◽  
Apurba Ghosh
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Adaptive Controller ◽  
Stability Control ◽  
Pendulum System ◽  
Stability Performance ◽  
Inverted Pendulum System ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

In this article, a stability analysis on an inverted pendulum system has been approached using a fractional order PID controller and a fractional order-based model reference adaptive controller. A modified MIT rule provides an extra degree of freedom, unlike an MIT rule of MRAC controllers to stablize the pendulum angle of the inverted pendulum system which is highly unstable in nature. Here, to analyze better stability performance of the inverted pendulum over the fractional order MIT rule of MRAC controller optimal fractional order, a PID controller has been approached and FMINCON numerical optimization algorithm has been chosen to optimize the fractional order PID controller using ITSE as a scaler objective function. Next, the behaviourial characteristics of the pendulum have been compared between the FMINCON-based FOPID controllers and the fractional order MIT rule of the MRAC controller to show robust performance using an optimal FOPID controller with respect to performance indices increases time, settling time, followed by errors ISE, IAE, ITSE.

scholarly journals Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller

2021 ◽  
Vol 11 (15) ◽  
pp. 6693
Author(s):  
Sagar Gupta ◽  
Abhaya Pal Singh ◽  
Dipankar Deb ◽  
Stepan Ozana
Keyword(s):  
Kalman Filter ◽  
Fractional Order ◽  
Pid Controller ◽  
Degree Of Freedom ◽  
Flexible Link ◽  
System Properties ◽  
Tool Position ◽  
Fractional Order Pid ◽  
Two Degree Of Freedom ◽  
Fractional Order Pid Controller

Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.

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