Abstract: A nonlinear model of the mathematical fluid dynamics which describes the motion of an incompressible viscous rotating fluid in a homogeneous gravitational field is considered. The model is a generalization of the known Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density. An explicit algorithm for the solution is constructed, and the proof of the existence and uniqueness theorems for the strong solution of the nonlinear problem is given. For the linear case, the localization and the structure of the spectrum of inner waves are also investigated.
Abstract: This paper investigates simple implicit force control
algorithms realizable with industrial robots. A lot of approaches
already published are difficult to implement in commercial robot
controllers, because the access to the robot joint torques is necessary
or the complete dynamic model of the manipulator is used. In
the past we already deal with explicit force control of a position
controlled robot. Well known schemes of implicit force control are
stiffness control, damping control and impedance control. Using such
algorithms the contact force cannot be set directly. It is further
the result of controller impedance, environment impedance and
the commanded robot motion/position. The relationships of these
properties are worked out in this paper in detail for the chosen
implicit approaches. They have been adapted to be implementable
on a position controlled robot. The behaviors of stiffness control
and damping control are verified by practical experiments. For this
purpose a suitable test bed was configured. Using the full mechanical
impedance within the controller structure will not be practical in the
case when the robot is in physical contact with the environment. This
fact will be verified by simulation.
Abstract: This study proposes the transformation of nonlinear
Magnetic Levitation System into linear one, via state and feedback
transformations using explicit algorithm. This algorithm allows
computing explicitly the linearizing state coordinates and feedback
for any nonlinear control system, which is feedback linearizable,
without solving the Partial Differential Equations. The algorithm is
performed using a maximum of N-1 steps where N being the
dimension of the system.