This paper proposes a novel design of a reconfigurable parallel kinematic manipulator used for a machine tool. After investigating the displacement and inverse kinematics of the proposed manipulator, it is found that the parasitic motions along x-, y-, and θ z -axes can be eliminated. The system stiffness of the parallel manipulator is conducted. In order to locate the highest system stiffness, single and multiobjective optimizations are performed in terms of rotation angles in xand y-axes and translation displacement in z-axis. Finally, a case study of tool path planning is presented to demonstrate the application of stiffness mapping. Through this integrated design synthesis process, the system stiffness optimization is conducted with Genetic Algorithms. By optimizing the design variables including end-effector size, base platform size, the distance between base platform and middle moving platform, and the length of the active links, the system stiffness of the proposed parallel kinematic manipulator has been greatly improved.
This paper presents a comparative study of three optimization algorithms, namely Genetic Algorithms (GAs), Pattern Search Algorithm (PSA) and Sequential Quadratic Program (SQP), for the design optimization of vehicle suspensions based on a quarter-vehicle model. In the optimization, the three design criteria are vertical vehicle body acceleration, suspension working space, and dynamic tire load. To implement the design optimization, five parameters (sprung mass, un-sprung mass, suspension spring stiffness, suspension damping coefficient and tire stiffness) are selected as the design variables. The comparative study shows that the global search algorithm (GA) and the direct search algorithm (PSA) are more reliable than the gradient based local search algorithm (SQP). The numerical simulation results indicate that the design criteria are significantly improved through optimizing the selected design variables. The effect of vehicle speed and road irregularity on design variables for improving vehicle ride quality has been investigated. A potential design optimization approach to the vehicle speed and road irregularity dependent suspension design problem is recommended.
This paper presents optimizations of a parallel kinematic manipulator used for a machine tool in terms of its workspace and stiffness. The system stiffness and workspace of the parallel manipulator are conducted in the paper. In order to locate the maximum system stiffness and workspace, single and multi objective optimizations are performed in terms of rotation angles in x and y axes and translation displacement in z axis with Genetic Algorithms. By optimizing the design variables including geometric dimensions of the manipulator, the system stiffness and workspace of the proposed parallel kinematic manipulator has been greatly improved.
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