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NPTEL

Control Engineering for Robotics

NPTEL via Swayam

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Overview

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ABOUT THE COURSE:This course offers a practical and design-oriented approach to classical and modern control theory, with a strong emphasis on applications in robotics. Rather than focusing solely on theoretical aspects, the course is structured to guide students through the process of controller design for dynamic systems, particularly robotic platforms. It is divided into two main components: classical control and modern control. The classical portion begins with system modeling and progresses to the design of P, PI, and PID controllers. The modern control section covers state- space representation, controllability, observability, pole placement, and optimal control using the Linear Quadratic Regulator (LQR).INTENDED AUDIENCE: Undergraduate BTech/BE, MTech/ME/PhD students in robotics and allied field.INDUSTRY SUPPORT: Aerospace, Robotics, Drones, Process Engineering, Power Systems based industry

Syllabus

Week 1:Mathematical Modeling of Physical Systems
  1. Laplace Transform.
  2. Transfer function.
  3. Mathematical Modeling from first principles.
    1. DC motor.
    2. Robotic arm.
    3. Quadrotor.
Week 2:Transfer functions and Time-domain analysis
  1. Transfer functions from experimental measurements.
  2. Bode plots.
  3. Transfer functions and Bode plot.
  4. Time domain analysis of system.
  5. Time-domain simulation of a quadrotor in 1D.
Week 3:Poles, zeros, and time-domain analysis
  1. Effect of poles and zeros on response
  2. Steady state error
  3. Closed loop poles and Root locus
  4. Introduction to root locus
  5. Root locus of a linearized quadrotor model
Week 4:Stability and PID Controller
  • BIBO Stability
  • PID controller
  • Design of PID controller
  • Effect of PID on a 1D-quadrotor model
Week 5: ControllerDesign (PID)
  • MATLAB based design of controllers
  • Design of speed controller and position controller of DC motor experimentally.
  • Importance of speed control in quadrotors
Week 6:State-space analysis
  • State-space modeling of system
  • Solution of state equations
  • State-space equations of a quadrotor
Week 7:Controllability
  • Solution of state equations continued
  • Introduction to controllability
  • Linearization of the quadrotor model and discussion on controllability
Week 8:Pole placement
  • Concept of state feedback and pole-placement
  • Ackermann’s formula
  • Simulation with the quadrotor example
Week 9:Observers and Observability
  • State observer (or estimator) design
  • Separation principle
  • Observer-based state feedback controller design
  • Discussions on need of an observer in a quadrotor
Week 10:Introduction to optimal control
  • Optimal control problem
  • LQR problem and its Solution
  • MATLAB Simulation with the quadrotor example
Week 11:Robotic Arm
  • Controller for a simple robotic arm
Week 12:Drones
  • Controller for Drones

Taught by

Prof. Chayan Bhawal

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