In this thesis, a methodology for rigid body dynamic modeling and control design is presented for a 6 degree-of-freedom (DOF) parallel-kinematic-mechanism-based reconfigurable meso-milling machine tool (RmMT) with submicron tracking accuracy requirement. The dynamic modeling of the parallel kinematic mechanism (PKM) is formulated using the Lagrangian method with the application of principle of energy equivalence and coordinate transformations to separate the mechanism into serial sub-systems. The rigid body gyroscopic force is also modeled using this approach and its effect as a disturbance is analyzed and compensated. The contour errors for both position and orientation are formulated to increase machining accuracy. The dynamic model of the system is linearized through feedback linearization and the contour error based feedback control law is formulated using the convex combination design approach to satisfy a set of design specifications simultaneously. The dynamic model and its control methodology are simulated and verified within the MATLAB Simulink environment.

In this thesis, a methodology for rigid body dynamic modeling and control design is presented for a 6 degree-of-freedom (DOF) parallel-kinematic-mechanism-based reconfigurable meso-milling machine tool (RmMT) with submicron tracking accuracy requirement. The dynamic modeling of the parallel kinematic mechanism (PKM) is formulated using the Lagrangian method with the application of principle of energy equivalence and coordinate transformations to separate the mechanism into serial sub-systems. The rigid body gyroscopic force is also modeled using this approach and its effect as a disturbance is analyzed and compensated. The contour errors for both position and orientation are formulated to increase machining accuracy. The dynamic model of the system is linearized through feedback linearization and the contour error based feedback control law is formulated using the convex combination design approach to satisfy a set of design specifications simultaneously. The dynamic model and its control methodology are simulated and verified within the MATLAB Simulink environment.

Parallel Kinematic Mechanisms (PKMs) are well suited for high-accuracy applications such as meso-milling. However, drawbacks such as limited platform tilting angle and high configuration dependency of stiffness often limit their usage. In this Thesis, a new six degree-of-freedom (dof) PKM architecture based on a 3×PPRS topology is proposed, in order to address these problems. The new PKM is presented, and its inverse kinematics and Jocobian matrix are derived. The kinematic relations are incorporated into MATLAB to calculate the workspace of the PKM. The stiffness of the new PKM is obtained using Finite Element Analysis (FEA), and configuration dependency of stiffness is investigated. The proposed new mechanism is compared with three similar existing 6-dof PKMs, and it is shown that the new PKM exhibits higher stiffness. Lastly, three meso-Milling Machine Tool prototypes were designed and built. In particular, Prototype III is based on the new mechanism.

Parallel Kinematic Mechanisms (PKMs) are well suited for high-accuracy applications such as meso-milling. However, drawbacks such as limited platform tilting angle and high configuration dependency of stiffness often limit their usage. In this Thesis, a new six degree-of-freedom (dof) PKM architecture based on a 3×PPRS topology is proposed, in order to address these problems. The new PKM is presented, and its inverse kinematics and Jocobian matrix are derived. The kinematic relations are incorporated into MATLAB to calculate the workspace of the PKM. The stiffness of the new PKM is obtained using Finite Element Analysis (FEA), and configuration dependency of stiffness is investigated. The proposed new mechanism is compared with three similar existing 6-dof PKMs, and it is shown that the new PKM exhibits higher stiffness. Lastly, three meso-Milling Machine Tool prototypes were designed and built. In particular, Prototype III is based on the new mechanism.