Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

A parallel manipulator is a closed loop mechanism which consists of a moving platform that is connected to a fixed base by at least two kinematic chains in parallel. Parallel manipulators can provide several advantages, such as high stiffness, high accuracy, and low inertia but also have some disadvantages, such as small workspace, complicated structures, a high cost, and also pose a major challenge to their analysis and control. To overcome the above shortcomings, progress on the development of parallel manipulators with less than 6-DOF has been accelerated. In this thesis, a new parallel manipulator with three degrees of freedom DOF is designed. Kinematic of the manipulator including inverse kinematic, Jacobian matrix and velocity equation are analyzed. Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. A prototype was fabricated to demonstrate the manipulator. An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN…