Multi-objective Fractional Order Controller Design with Evolutionary Algorithms

Author(s):  
Indranil Pan ◽  
Saptarshi Das
2013 ◽  
Vol 313-314 ◽  
pp. 544-548 ◽  
Author(s):  
Mehmet Korkmaz ◽  
Omer Aydogdu

Fractional order controllers which has mostly used recently have investigated in this paper. It is benefit from ball & beam system to show effects of controllers. Fractional order controller and its integer form are compared with simulation results for the mentioned system. Parameters of controllers have obtained by using evolutionary algorithms techniques which are particle swarm optimization (PSO) and genetic algorithms (GAs). According to results, it is confirmed the advantage of fractional controllers. Beside, PSO has a little bit superiority over GAs technique for determining optimum values of controller parameters.


2018 ◽  
Vol 51 (4) ◽  
pp. 912-917 ◽  
Author(s):  
Eva-H. Dulf ◽  
Mircea Șușcă ◽  
Levente Kovács

Mathematics ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 1166 ◽  
Author(s):  
Eva-Henrietta Dulf

Classical fractional order controller tuning techniques usually establish the parameters of the controller by solving a system of nonlinear equations resulted from the frequency domain specifications like phase margin, gain crossover frequency, iso-damping property, robustness to uncertainty, etc. In the present paper a novel fractional order generalized optimum method for controller design using frequency domain is presented. The tuning rules are inspired from the symmetrical optimum principles of Kessler. In the first part of the paper are presented the generalized tuning rules of this method. Introducing the fractional order, one more degree of freedom is obtained in design, offering solution for practically any desired closed-loop performance measures. The proposed method has the advantage that takes into account both robustness aspects and desired closed-loop characteristics, using simple tuning-friendly equations. It can be applied to a wide range of process models, from integer order models to fractional order models. Simulation results are given to highlight these advantages.


Author(s):  
G. Kannayeram ◽  
P.S. Manoharan ◽  
M. Willjuice Iruthayarajan ◽  
T. Sivakumar

Author(s):  
Amir Hajiloo ◽  
◽  
Wen-Fang Xie

The design of the optimal fuzzy fractional-order PID controller is addressed in this work. A multi-objective genetic algorithm is proposed to design rule base and membership functions of the fuzzy logic systems. Three conflicting objective functions in both time and frequency domains have been used in Pareto design of the fuzzy fractional-order PID controller. The simulation results reveal the effectiveness of the proposed method in comparison with the results produced by the fractional-order PID controllers.


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