Optimal Stabilization Control Of Autonomous Helicopter Using Genetic Algorithm in C Language Environment

Tan, Teck Seong (2010) Optimal Stabilization Control Of Autonomous Helicopter Using Genetic Algorithm in C Language Environment. Project Report. UTeM, Melaka, Malaysia. (Submitted)

	PDF (24 pages) Optimal_Stabilization_Control_Of_Autonomous_Helicopter_Using_Genetic_Algorithm_in_C_Language_Environment_-_24_pages.pdf - Submitted Version Download (584kB)
	PDF (Full Text) Optimal_Stabilization_Control_Of_Autonomous_Helicopter_Using_Genetic_Algorithm_in_C_Language_Environment_-_Full_Text.pdf - Submitted Version Restricted to Registered users only Download (3MB)

Abstract

This research presents the stability control of prototype helicopter using Genetic Algorithm (GA) to obtain optimization. Since the movement of prototype helicopter is complicated, this is very difficult to control the stability of prototype helicopter with traditional methods. The design strategy is to employ the GA to search the optimized parameters of the stability control. The GA is developed in C language environment and optimized sensors data as input is implemented into microcontroller to control rotors to achieve the stability and balancing movement control. The compiler software that are used comprise of Dev – C++, which is used to compile the GA functions in C programming and analyze the results of GA functions based on the different input parameters and fitness function. Quincy 2005 software that is used to plot the graph of data that created by the GA functions in C language environment since Quincy possesses integrated Koolplot 2D plotting library, CCS C Compiler is used to program coding into microcontroller. The software that will be used to draw the schematic and PCB design is Protel 99 SE. The purpose of using Protel 99 SE is to create a prototype for validation and testing of GA program. GA is developed in C language followed by compiling and debugging. The real time testing is carried out to validate the coding programmed. A graph of fitness value versus generation is plotted in order to find optimum value. The optimum value will be used as input for controlling motors as autonomous helicopter is capable to achieve stability. The time taken for autonomous helicopter to achieve stability depends on number of generations that are executed.

Actions (login required)

View Item