Intelligent Control Techniques for Precise Landing Operation of UAV on Unstable Liquid Surfaces

Abstract

The Rocket landing surface, based on the ball balancer system, is a highly nonlinear and complex problem that uses a modern artificial intelligence method to land a rocket on an unsteady surface. This detailed study compares proportional-integral (PI) controllers, traditional fuzzy controllers with triangle membership functions, and hybrid membership fuzzy controllers for this difficult application. In crucial measures, including rise time, settling time, and overshoot, the hybrid membership fuzzy controller leads. This controller responds faster, settles faster, and reduces overshoot. Its stability and precision make it ideal for rocket landings on unstable surfaces. Artificial intelligence-based Fuzzy logic control can improve the operating efficiency of complex systems with non-linear and underactuated features, such as ball balancer systems for rocket landings. The work acknowledges that defining accurate AI-based fuzzy logic standards and selecting appropriate membership functions is difficult. Due to the latent potential of fuzzy logic control in complex systems, the findings suggest more research and development. Fuzzy logic control, supported by artificial intelligence, is a promising control technology for engineering and robotics applications, improving rocket landings in dangerous terrain.