Robust Controller Design Using Genetic Algorithm with Visualization Capabilities

For the given system, we have developed a robust controller based on genetic algorithms along with a comprehensive plotting program. The controller design focuses on enhancing system robustness and performance metrics. Our implementation utilizes genetic algorithms as the core optimization method, which automatically tunes controller parameters to achieve superior robustness against uncertainties and disturbances. The algorithm operates through selection, crossover, and mutation operations to evolve optimal controller configurations. The accompanying visualization program generates plots of system input and output signals, employing MATLAB's plotting functions to display time-domain responses and frequency characteristics. This enables better understanding of system behavior and performance evaluation. Through this integrated design approach and software tools, we achieve improved control over the specified system while facilitating deeper research and analysis. The code includes functions for fitness evaluation, population management, and graphical representation of results.