Model Simplification For Dynamic Control of SeriesParallel Hybrid Robots  A Representative Study on the Effects of Neglected Dynamics Shivesh It is becoming increasingly popular to use parallel mechanisms as modular subsystem units in the design of various robots for their superior stiffness, payloadtoweight ratio and dynamic properties. This leads to seriesparallel hybrid robotic systems which pose several challenges in their modeling and control e.g. resolution of loop closure constraints, large size of their spanning tree etc. These robots are typically positioncontrolled and when equipped with real time dynamic control, often a simplified inverse dynamic model of these systems is utilized. However, the tradeoffs of this model simplification has not been studied previously. This paper presents a representative study of the neglected dynamics by introducing some error metrics which are useful in highlighting the advantages and disadvantages of such model simplification. The study is guided with the help of a seriesparallel humanoid leg which has been recently developed at DFKIRIC.

Decoupling Control and Simulation of a 3RSR Spheroid Parallel Wrist The control of position and trajectory tracking are critical issues in parallel robots. Traditional PID tracking algorithms, which are based on kinematics control use the position and speed deviation as a negative feedback in order to design a controller. However, this method is not only hard to maintain the excellent dynamic and static quality of a system, but it is also incapable of realizing complete decoupling, and it needs large energy to be controlled. To overcome such drawbacks, this paper proposes, a computed torque decoupling control strategy for a 3RSR spheroid parallel mechanism. The control strategy includes a computed torque decoupling control method with traditional PD controller and selfadaption fuzzy controller. It was proved that the corresponding Lyapunov function is global asymptotic stable in the ideal and nonideal estimation. A set of ADAMSMATLAB dynamic simulations were established based on virtual prototyping technology. The results demonstrated that the performance of the control scheme with selfadaption fuzzy controller is more effective than that with PD controller.