Specification of a control system fitness function using constraints for genetic algorithm based design methods

1995 ◽  
Author(s):  
G.J. Gray
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Fitness Function ◽  
Design Methods

Control System Modeling for Automotive Brake Test-Bench Based on Improved PID Algorithm

2012 ◽  
Vol 542-543 ◽  
pp. 1007-1010
Author(s):  
Jia Xi Du ◽  
Hong Shen ◽  
Yuexia Feng
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Pid Control ◽  
Test Bench ◽  
Control Function ◽  
Fitness Function ◽  
System Modeling ◽  
Loop Model ◽  
Deviation Function ◽  
Automotive Brake

Based on PID controller, the closed-loop model of instantaneous torque for automotive brake test-bench was established, and then the instantaneous torque and the deviation function were calculated, furthermore, the genetic algorithm was adopted in order to get a global optimal solution and to optimize the parameters of the PID control system. So that the deviation function can be reduced or improved. By comparing the effect of control function, the causes for error volatility of the PID control system were derived, and the fitness function of genetic algorithm was determined reasonably. This algorithm can improve the reliability and accuracy of the control model effectively, and provide an effective method for testing the merits and integrated performance of automotive brake design.

scholarly journals Optimization of the PID coefficients for the line-follower mobile robot controller employing genetic algorithm

Informatics ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. 53-68
Author(s):  
T. Yu. Kim ◽  
R. A. Prakapovich
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Mobile Robot ◽  
Software Package ◽  
Pid Controller ◽  
Fitness Function ◽  
Color Contrast ◽  
Robot Controller ◽  
Mobile Robot Control ◽  
Evolutionary Tuning

O b j e c t i v e s. To develop a control system for the movement of a mobile robot along a color-contrast line, as well as to find the values of the coefficients of a proportional-integral-differentiating (PID) controller that allows the robot to move along the line at a given speed.M e t ho d s. To adjust the values of the coefficients of the PID controller, methods of enumeration, automatic tuning and a genetic algorithm are used.Re s u l t s. A software package for tuning the PID controller of the educational mobile robot RoboCake, designed to move along a closed color-contrast line at a given speed, has been developed. The software package consists of a simulation model of the specified robot in the Simulink environment, several virtual traces-polygons and a specialized solver based on the developed genetic algorithm. With the help of the proposed fitness function, a mobile robot control system that satisfies the stated conditions is implemented. Based on the conducted model experiments, the desired values of the parameters of the PID controller are obtained.Co n c l u s i o n. A comparison of the effectiveness of various methods of tuning the PID controller is carried out. The developed software package is designed to solve the practical problem of moving a mobile robot along a color-contrast line at a speed of 1 m/s. The results obtained can be used to study methods of evolutionary tuning of stabilization systems for transport robots, ensuring their movement without overshoot.

scholarly journals Application of Genetic Algorithm Elements to Modelling of Rotation Processes in Motion Transmission Including a Long Shaft

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 115
Author(s):  
Andriy Chaban ◽  
Marek Lis ◽  
Andrzej Szafraniec ◽  
Radoslaw Jedynak
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Fitness Function ◽  
Least Square ◽  
Distributed Parameter ◽  
Parameter Method ◽  
Analytical Mechanics ◽  
Parameter System ◽  
Rotational Systems ◽  
Elastic Elements

Genetic algorithms are used to parameter identification of the model of oscillatory processes in complicated motion transmission of electric drives containing long elastic shafts as systems of distributed mechanical parameters. Shaft equations are generated on the basis of a modified Hamilton–Ostrogradski principle, which serves as the foundation to analyse the lumped parameter system and distributed parameter system. They serve to compute basic functions of analytical mechanics of velocity continuum and rotational angles of shaft elements. It is demonstrated that the application of the distributed parameter method to multi-mass rotational systems, that contain long elastic elements and complicated control systems, is not always possible. The genetic algorithm is applied to determine the coefficients of approximation the system of Rotational Transmission with Elastic Shaft by equivalent differential equations. The fitness function is determined as least-square error. The obtained results confirm that application of the genetic algorithms allow one to replace the use of a complicated distributed parameter model of mechanical system by a considerably simpler model, and to eliminate sophisticated calculation procedures and identification of boundary conditions for wave motion equations of long elastic elements.

scholarly journals Hybrid Optimization Based Mathematical Procedure for Dimensional Synthesis of Slider-Crank Linkage

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1581
Author(s):  
Alfonso Hernández ◽  
Aitor Muñoyerro ◽  
Mónica Urízar ◽  
Enrique Amezua
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Linear Equations ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Dimensional Synthesis ◽  
Hybrid Strategy ◽  
Dimensional Parameters ◽  
Optimization Methodology ◽  
Crank Mechanism

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.

AN EVOLUTIONARY APPROACH FOR IMPUTING MISSING DATA IN TIME SERIES

2010 ◽  
Vol 19 (01) ◽  
pp. 107-121 ◽  
Author(s):  
JUAN CARLOS FIGUEROA GARCÍA ◽  
DUSKO KALENATIC ◽  
CESAR AMILCAR LÓPEZ BELLO
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Missing Data ◽  
Genetic Structure ◽  
Evolutionary Algorithm ◽  
Fitness Function ◽  
Error Function ◽  
Missing Observations ◽  
Mean And Variance ◽  
Methodological Aspects

This paper presents a proposal based on an evolutionary algorithm for imputing missing observations in time series. A genetic algorithm based on the minimization of an error function derived from their autocorrelation function, mean, and variance is presented. All methodological aspects of the genetic structure are presented. An extended description of the design of the fitness function is provided. Four application examples are provided and solved by using the proposed method.

Solving Vibration Control Problems Using Reduced Order Models for Flexible Structures: A Genetic Algorithm Approach

1997 ◽  
Author(s):  
Sourav Kundu ◽  
Kentaro Kamagata ◽  
Shigeru Sugino ◽  
Takeshi Minowa ◽  
Kazuto Seto
Keyword(s):  
Genetic Algorithm ◽  
Vibration Control ◽  
Controller Design ◽  
Fitness Function ◽  
Flexible Structures ◽  
Design Solution ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Fitness Value ◽  
Genetic Algorithm Approach

Abstract A Genetic Algorithm (GA) based approach for solution of optimal control design of flexible structures is presented in this paper. The method for modeling flexible structures with distributed parameters as reduced-order models with lumped parameters, which has been developed previously, is employed. Due to some restrictions on controller design it is necessary to make a reduced-order model of the structure. Once the model is established the design of flexible structures is considered as a feedback search procedure where a new solution is assigned some fitness value for the GA and the algorithm iterates till some satisfactory design solution is achieved. We propose a pole assignment method to determine the evaluation (fitness) function to be used by the GA to find optimal damping ratios in passive elements. This paper demonstrates the first results of a genetic algorithm approach to solution of the vibration control problem for practical control applications to flexible tower-like structures.

Towards Academic Successor Selection Modelling with Genetic Algorithm in Multi-Criteria Problems

2018 ◽  
Vol 7 (4.33) ◽  
pp. 130
Author(s):  
Atiqa Zukreena Zakuan ◽  
Shuzlina Abdul-Rahman ◽  
Hamidah Jantan ◽  
. .
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Succession Planning ◽  
Fitness Function ◽  
Academic Staff ◽  
Fitness Value ◽  
Selection Decision ◽  
The University ◽  
Hierarchy Process

Succession planning is a subset of talent management that deals with multi-criteria and uncertainties which are quite complicated, ambiguous, fuzzy and troublesome. Besides that, the successor selection involves the process of searching the best candidate for a successor for an optimal selection decision. In an academic scenario, the quality of academic staff contributes to achieving goals and improving the performance of the university at the international level. The process of selecting appropriate academic staff requires good criteria in decision-making. The best candidate's position and criteria for the selection of academic staff is the responsibility of the Human Resource Management (HRM) to select the most suitable candidate for the required position. The various criteria that are involved in selecting academic staff includes research publication, teaching skills, personality, reputation and financial performance. Previously, most studies on multi-criteria decision-making adopt Fuzzy Analytical Hierarchy Process (FAHP). However, this method is more complex because it involved many steps and formula and may not produce the optimum results. Therefore, Genetic Algorithm (GA) is proposed in this research to address this problem in which a fitness function for the successor selection is based on the highest fitness value of each chromosome.    

Sign in / Sign up

Export Citation Format

Share Document