scholarly journals On the Computational Analysis of the Genetic Algorithm for Attitude Control of a Carrier System

2018 ◽  
Author(s):  
Hadi Jahanshahi ◽  
Naeimeh Najafizadeh Sari
Keyword(s):  
Genetic Algorithm ◽  
Attitude Control ◽  
Computational Analysis ◽  
Carrier System

scholarly journals Genetic algorithms for GNC settings and DACS design application to an asteroid Kinetic Impactor

2018 ◽  
Author(s):  
P. Vernis ◽  
V. Oliviero
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Control System ◽  
Attitude Control ◽  
Medium Size ◽  
Attitude Control System ◽  
Data Set ◽  
Earth Object ◽  
Navigation And Control ◽  
And Control

This paper deals with an application of Genetic Algorithm (GA) tools in order to perform and optimize the settings phase of the Guidance, Navigation, and Control (GNC) data set for the endgame phase of a Kinetic Impactor (KI) targeting a medium-size Near Earth Object (NEO). A coupled optimization of the GNC settings and of the GC-oriented design of the Divert and Attitude Control System (DACS) is also proposed. The illustration of the developed principles is made considering the NEOShield study frame.

Design of Longitudinal Optimal Controller in Unmanned Helicopter Based on Genetic Algorithm

2011 ◽  
Vol 317-319 ◽  
pp. 690-693
Author(s):  
Wei Ping Zhao ◽  
Dong Zhou Yu ◽  
Zhan Shuang Hu
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Attitude Control ◽  
Research Direction ◽  
Unmanned Helicopter ◽  
Attitude Control System ◽  
Main Research ◽  
Accuracy Requirement ◽  
Optimal Value ◽  
Small Unmanned Helicopter

In this paper, the main research direction of optimal control is aimed at mathematical model of small unmanned helicopter longitudinal channels. Genetic algorithm was used to optimize the select of control law which is tolerance, make small unmanned helicopter operate as given requirements, and make the given performance index achieve optimal value (minimum or maximum). This paper will introduce the optimal control theory to attitude control system of small unmanned helicopter. The simulation results prove that this method can well satisfy the control accuracy requirement of small unmanned helicopter attitude system.

Optimal Tuning of Single-Axis Satellite Attitude Control Parameters Using Genetic Algorithm

2020 ◽  
Author(s):  
Nasser Khalili ◽  
Amin Ghorbanpour
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Fuel Consumption ◽  
Attitude Control ◽  
Pulse Frequency ◽  
Control Parameters ◽  
Control Loop ◽  
Arbitrary Initial Condition ◽  
Novel Approach ◽  
Satellite Attitude Control

Abstract This paper studies the optimization of control parameters for single-axis attitude control of a rigid satellite using thrusters. It is desired to tune the control parameters to minimize the number of thruster firings. The motion task is defined as an attitude pointing maneuver from arbitrary initial condition to the rest. To this end, a control loop with pulse-width pulse-frequency modulator is suggested. The control actuators are pairs of identical non-ideal thrusters which each one produces torque in one direction around the control axis. A novel approach is proposed to model the dynamics of thruster with a design parameter which shapes the response of the actuator. Nine parameters of the control loop, e.g. feedback gains, modulator parameters, and thruster dynamics, are selected as decision variables. Genetic algorithm is used to find the optimal values of the variables such that the firing is minimized. It is shown that firing minimization requires a sluggish thruster. Moreover, to study the effect of deviation from optimal value on number of thruster firings and fuel consumption, a sensitivity analysis is performed. Based on sensitivity analysis, an optimal range is suggested for each parameter where both number of firing and fuel consumption are minimized.

Time Optimal and Time-Energy Optimal Control of Satellite Attitude Using Genetic Algorithms

2002 ◽  
Author(s):  
Kittipong Boonlong ◽  
Nachol Chaiyaratana ◽  
Suwat Kuntanapreeda
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Genetic Algorithms ◽  
Attitude Control ◽  
Control Problems ◽  
Attitude Control System ◽  
Satellite Attitude ◽  
Satellite Attitude Control ◽  
Time Optimal ◽  
Single Objective

This paper presents the use of genetic algorithms for solving time optimal and time-energy optimal control problems in a satellite attitude control system. The satellite attitude control system is a multi-input/multi-output non-linear system at which its continuous attitude-related states are driven by discrete-valued command torque input. The problems investigated cover the time optimal control with two-state input (−u, +u) and three-state input (−u, 0, u) and the time-energy optimal control with three-state input. With the use of two-state input, the control problem has been formulated as a multi-objective optimisation problem where the decision variables are composed of the time where an input-state switching occurs while the objectives consist of the final state errors and the trajectory time. A multi-objective genetic algorithm (MOGA) has been successfully used to obtain the time optimal solution which is superior to that generated by linearising the system and utilising a bang-bang control law. In contrast, with the use of three-state input, the control problems are reduced to single-objective optimisation problems. In the case of time optimal control, the objective is the trajectory time while a time-energy cost is used as the search objective in the time-energy optimal control. A single-objective genetic algorithm has been successfully used to generate the optimal control solutions for both problems. In addition, the effects of diversity control on the genetic algorithm performances in the control problems have also been identified.

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