Simulation And Optimization Of6-DOF Stewart Parallel Manipulator

Six-degree-of-freedom parallel manipulator is Stewart parallel manipulator.Compared to the serial manipulator, parallel manipulator with advantages of highprecision, stiffness, large loading capacity, fast system dynamic response as well as thecumulative error is small, etc. It becomes a hot research direction of domestic andforeign scholars in recent years. And it is widely applied to the field of robots andparallel machine tools and Aeronautics and Astronautics. Stewart parallel manipulatorhas many advantages, but its own obvious shortcomings, because of its unique structure,strong coupling movement characteristics between the actuator. Parallel mechanism isaccompanied by the shortcomings of the singular positions and poor flexibility. In orderto try to avoid or reduce the impact of the disadvantages of institutional performance,we need to optimize the Stewart parallel manipulator. It is essential that depthunderstanding of the kinematics and dynamics of the Stewart parallel manipulator.Firstly, this paper analyzed the kinematics and dynamics of Stewart parallelmanipulator, and derived the kinematics equation by inverse kinematics solutions. Itestablished single body dynamics equations by Newton-Euler method and multi-bodydynamics equations by Kane’s method. And it presented the performance evaluation ofthe Stewart parallel manipulator, as good theoretical preparation for the structuraloptimization.Secondly, this paper parametrically modeled Stewart parallel manipulator usingADAMS software, and carried out kinematics and dynamics simulation. ADAMSsimulation results are compared with the theoretical calculation results verified thecorrectness of single body dynamics model and multi-body dynamics model.Finally, this paper optimized the structure of Stewart parallel manipulator. Beforeoptimization it qualitatively analyzed the impact of the structural parameters on systemperformance. It initially identified the preferable range of the structural parameters.Then using the Genetic Algorithm automatically optimized the determined objectivefunction, obtained specific optimization results. And it compared the optimized resultswith the previous results.