Multidisciplinary Engineering systems are
complex and carry increased risk, development time and integration challenges.
Model-based system design helps to manage the complexity and enhance
integration while reducing the development time and risk. But just how does
model-based design improve the process of choosing a motor for a motion
application?
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First of all, consider that
system requirements dictate a desired end-point trajectory. ?The motion can
be defined as an electronic cam, characterized by different profiles and
maximum values of velocity, acceleration and jerk, which will affect the level
of mechanical stress, vibration and noise in the motor, transmission system and
mechanical load. It is therefore essential that the desired motion profile be
chosen first, because the required torque versus speed curve to size the motor
depends on it. In addition, the motion profile has relevant implications on the
tracking errors through the control system. ?A kinematic (geometry of motion) model of the
mechanical system is then developed and, through inverse kinematics, the
required motor motion profile is determined. The torque-speed requirements for
the motor are determined by first developing a kinetic (geometry plus all
torques and mass moments of inertia) model of the complete mechanical system
and then applying an appropriate feedback control system (e.g., PID) to that
model. ?A
computer simulation (e.g., MatLab Simulink) of the mechanical and control
systems will result in the necessary torque-speed curve of the load to size the
motor.
Once this process is complete, candidate servo motors (e.g.,
permanent-magnet synchronous motors) can be identified. Additional
requirements, such as cost, energy efficiency and load-to-motor inertia ratio,
will shorten the list. The chosen motor, including any flexible couplings or
gearing, becomes an integral part of the system, and its properties must be
included in the system model. The control system will have to be tuned or even
modified because of the motor addition.
A computer simulation will reveal new torque-speed requirements
for the system by presenting a number of issues to address. Is the motor's
torque-speed capability satisfactory? Is the control system stable? Does the
system meet application-specific requirements regarding time response, relative
stability and steady-state error? If the answer to any of these questions is
no, iteration is required.
With all of these factors addressed in detail, a model-based
design approach, together with computer simulation, can lead to optimal motor
selection and all the benefits that implies to overall system performance.
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