Exploiting Fractional Order PID Controller Methods in Improving the Performance of Integer Order PID Controllers: A GA Based Approach

2009 ◽  
Author(s):  
Bijoy K. Mukherjee ◽  
Santanu Metia ◽  
Sio-Iong Ao ◽  
Alan Hoi-Shou Chan ◽  
Hideki Katagiri ◽  
...  
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Pid Controllers ◽  
Integer Order ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

An Enhanced Robust Fractional Order PID Controller for Electric Machinery System: Tuning Rules and Simulations

2015 ◽  
Author(s):  
Chunyang Wang ◽  
Meng Wu ◽  
Nianchun Cai ◽  
Xuelian Liu ◽  
Chengjun Tian
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Optimal Parameter ◽  
Design Method ◽  
Open Loop ◽  
Electrical Machinery ◽  
Integer Order ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller ◽  
Machinery System

A design method of enhanced robust fractional order PID controller is proposed to control electrical machinery system. Magnitude margin constraint, phase margin constraint and the gain robustness constraints of partly flat phase in specified dots around crossover frequency are adopted to design enhanced robust fractional order PID controller which has stronger robustness to open-loop gain variation compared with integer order PID controller. Besides, nonlinear optimization function is adopted to hunt for optimal parameter solutions of enhanced robust fractional order PID controller, so the five parameters of enhanced robust fractional order PID controller can be solved. The electrical machinery control system models are simulated and tested by MATLAB/SIMULINK, and the results show that the proposed fractional order PID controller has stronger robustness and smaller overshoot, compared with integer order PID controller.

Design of Fractional Order PID Controller Based on Artificial Immune Algorithm

2011 ◽  
Vol 268-270 ◽  
pp. 1061-1066 ◽  
Author(s):  
You Rui Huang ◽  
Hai Bo Hu
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Immune Algorithm ◽  
Pid Controllers ◽  
Time Varying ◽  
Artificial Immune ◽  
Artificial Immune Algorithm ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller ◽  
Method Of Design

PID control scheme has been widely used in most of control system. The method of design PID controller is mature gradually. Due to the controlled object is nonlinear and time-varying, so the integer PID controller can not achieve the desired effect. After study people found that the application of fractional order PID controllers can solve the problem of time-varying and nonlinear very well and the controller has high control precision. Currently, the method of design fractional order PID controllers is little. This article describes an artificial immune algorithm and using MATLAB for simulation, the simulation results demonstrate that the artificial immune algorithm has little error and high optimization speed than traditional optimization algorithm, and the fractional order PID controller has a better control effect than traditional integer PID controller.

scholarly journals Variable, Fractional-Order PID Controller Synthesis Novelty Method

2020 ◽  
Author(s):  
Piotr Ostalczyk ◽  
Piotr Duch
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Main Idea ◽  
Pid Controllers ◽  
Time Interval ◽  
Discrete Variable ◽  
Closed Loop Systems ◽  
The Stability ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

The novelty method of the discrete variable, fractional order PID controller is proposed. The PID controllers are known for years. Many tuning continuous time PID controller methods are invented. Due to different performance criteria there are optimized three parameters: proportional, integral and differentiation gains. In the fractional order PID controllers there are two additional parameters: fractional order integration and differentiation. In the variable, fractional order PID controller fractional orders are generalized to functions. Nowadays all PID controllers are realized by microcontrollers in a discrete time version. Hence, the order functions are discrete variable bounded ones. Such controllers offer better transient characteristics of the closed loop systems. The choice of the order functions is still the open problem. In this Section a novelty intuitive idea is proposed. As the order functions one applies two spline functions with bounded functions defined for every time subinterval. The main idea is that in the final time interval the variable, fractional order PID controller transforms itself to the classical one preserving the stability conditions and zero steady-state error signal. This means that in the last time interval the discrete integration order is −1 and differentiation is 1.

Pareto Optimal Robust Design of Fuzzy Fractional-Order Pid Controllers

2011 ◽  
Vol 403-408 ◽  
pp. 4735-4742
Author(s):  
Nader Nariman Zadeh ◽  
Amir Hajiloo
Keyword(s):  
Fractional Order ◽  
Robust Design ◽  
Pid Controller ◽  
Pid Controllers ◽  
Pareto Optimum ◽  
Pareto Optimal ◽  
Objective Functions ◽  
Trade Off ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

In this paper, a multi-objective uniform-diversity genetic algorithm (MUGA) is used for Pareto optimum design of fuzzy fractional-order PID controllers for plants with parametric uncertainties. Two conflicting objective functions have been used in Pareto design of the fuzzy fractional-order PID controller. The results clearly show that an effective trade-off can be compromisingly achieved among the different fuzzy fractional-order PID controllers obtained using the methodology of this work and to achieve a robust design against the plant’s uncertainties.

scholarly journals Design of a Fractional Order PID Controller for Electric Hydraulic Actuator

2021 ◽  
pp. 59-68
Author(s):  
Erinna Dyah Atsari ◽  
Abdul Halim
Keyword(s):  
Steady State ◽  
Fractional Order ◽  
Pid Controller ◽  
Pid Controllers ◽  
System Response ◽  
Hydraulic Actuator ◽  
Fluid Flow Control ◽  
Two Parameters ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

Electric hydraulic actuators are more used especially in industries that demand high levels of accuracy. A common problem with this type of actuator is consistency in fluid flow control. PID controllers can accelerate the achievement of defined output values, eliminate offsets, and reduce maximum overshoots but result in considerable errors. Therefore, it is necessary to design controllers that can reduce errors significantly. In this research, a Fractional Order PID controller is developed to reduce maximum overshoots and steady state. Unlike conventional PID controllers that have three  parameters, in the Fractional Order PID controller, there are extra two parameters of the λ and μ. The   parameters were selected using the Ziegler Nichols method with a 1st order approach with a delay time. Meanwhile, the λ and μ parameters were selected the best value to make the system response better. The results of the design of the Fractional Order PID controller were evaluated using matlab simulation. The simulation results showed that the Fractional Order PID controller was able to reduce the steady state error response by 0.5 %, and the maximum overshoots by 17.4 %. From this result, it can be noted that the Fractional Order PID controller is better than conventional PID.

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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