Optimization of sliding control parameters for a 3-dof robot arm using genetic algorithm (GA)

The ability to accurately control the motion of these manipulators is crucial for achieving desired tasks efficiently and reli ably. This paper focuses on the cylindrical manipulator, a type of robot arm that has three degrees of freedom (DOF) with the position of each joint computed from a trajectory in the Cartesian space using the inverse kinematic model that represents the rea l manipulator [1]. The cylindrical manipulator has many applications in industry, research and education, such as assembly, welding, painting, pick - and - place, testing, teaching and learning. However, controlling the cylindrical manipulator is a difficult t ask because of its nonlinear and uncertain dynamics, coupled with the presence of external disturbances and measurement noises. Robotic manipulators need to operate stably and efficiently, which requires understanding their trajectory and controlling and m onitoring them effectively.