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Course description :
Dynamical models for manipulator in Lagrange and Newton-Euler formulations.
Controller design based on manipulator dynamics.
PID-controllers, eigenvalue assignment and adaptive self-tuning control.
Controllers for compliant motion.
To familiarize students whit the various control algorithms for robotic
manipulator control. Design of deterministic
and adaptive controllers, and gross and fine motion controllers. Verify
the controller design by simulations.
Any text on robotics and manipulators
John J. Craig. Introduction to Robotics, Mechanics and Control,
2nd edition.
Any book / text on robotics and manipulators.
2 long exams 100 %
92 - 100 1.0
88 - < 92 1.25
84 - < 88 1.5
80 - < 84 1.75
76 - < 80 2.0
72 - < 76 2.25
68 - < 72 2.5
64 - < 68 2.75
60 - < 64 3.0
< 60
5.0
I. Class policies
A. Class requirements / expectations
B. Possible class projects
II. Dynamic models for manipulator motion
A. Lagrange's formulation
B. Newton-Euler formulation
C. State variable representation
III. Primary and secondary controller desing for gross motion
A. Desired trajectory generation
B. Design specifications
C. Controller design by eigenvalue assignment
D. Optimal controller for manipulators
IV. Adaptive control of manipulator gross motion
A. Self-tuning controller design by minimizing a
performance criterion
B. Manipulator control using model reference adaptive
contollers
V. Compliant motion control
A. Modeling and control of end-effector forces
B. PID-controllers for position, velocity and force
control
C. Adaptive position, velocity and force control
VI. Other topics
A. Coordinated multiple manipulators
B. Non-rigid manipulators
C. Redundant and underactuated manipulators