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Course Detail

Course Name Underactuated Robotics
Course Code 24RAI432
Program B.Tech. Artificial Intelligence (AI) and Data Science (Medical Engineering)
Semester VII
Credits 3
Campus Coimbatore

Syllabus

UNIT – I

Fully actuated vs Under-actuated Systems
Motivation and Definition of under-actuated control problem-Input and output state constraints- Non-holonomic Constraints-Case studies examples- simple pendulum-Humanoid robot, UAV and wheeled robots- Introduction to optimal control-Double-integrator examples

UNIT – II

Model Based Control
Pendulum case study-Nonlinear dynamics with constant torque-Equations of motion-Linearizing the manipulator equations-Controllability Factor-Linear Quadratic regulator (Hamilton-Jacobi-Bellman (HJB) sufficiency), Pontryagin’s min-time control

UNIT – III

Nonlinear Planning & Control-1
Formulating control design as an optimization-Continuous dynamic programming-HJB equation- Solving for minimizing control-Stabilization of nonlinear systems- Finite horizon control -Linear quadratic optimal tracking-LQR with input and output constraints- LQR as a convex optimization problem- LQG-Case studies- Pendulum

UNIT – IV

Nonlinear Planning & Control-2
Lyapunov functions-Relationships to HJB equations-Lyapunov analysis for linear and polynomial systems-Trajectory optimization problem- Feedback motion planning-Linear Quadratic Gaussian approach- Model predictive control approach

Course Objectives

Course Objectives:

  1. To enable learners to apply mathematics in the design of under-actuated robotic systems with a primary emphasis on linear quadratic regulator based predictive control and state estimation
  2. To train the students in applying the idea of optimal control to the design of under-actuated robotic control

Course Outcomes:

After completing this course, students will be able to:
CO1: Analyze nonlinear underactuated systems
CO2: Demonstrate simple robot models for walking and running
CO3: Simulate the dynamics and control of Highly articulated robots
CO4: Perform nonlinear planning and control of simple robot models

Online Material

1. MIT open course ware: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-832-underactuated-robotics-spring-2009/index.htm

CO-PO Mapping

PO/PSO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3
CO
CO1 3 3 2 1 3 3 3 2 3 2
CO2 3 3 1 1 3 1 3 3 1 2 1 3
CO3 3 3 3 2 3 1 3 3 2 3 2 3
CO4 3 3 3 2 3 3 3 2 3 1 3

References

  1. Brian D. O. Anderson and John B. Moore. Optimal Control: Linear Quadratic Methods. Dover Publications, 1st Edition, 2007.
  2. Bertsekas, Dimitri P. Dynamic Programming and Optimal Control. 3rd ed. Vols. I and II. Nashua, NH: Athena Scientific, 2007. ISBN: 9781886529083 (set).
  3. Donald.E.Kirk. Optimal Control Theory, Dover Publications,2004
  4. Fantoni, Isabelle, and Rogelio Lozano. Non-linear Control for Under-actuated Mechanical Systems. New York, NY: Springer-Verlag, 2002. ISBN: 9781852334239.
  5. Strogatz, Steven H. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Boulder, CO: Westview Press, 2001. ISBN: 9780738204536.
  6. Slotine, Jean-Jacques E., and Weiping Li. Applied Nonlinear Control. Upper SaddleRiver, NJ: Prentice Hall, 1991. ISBN: 9780130408907

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