
Learning outcomes:
The student is able to…
 Linearize a nonlinear system around an operating point and obtain its statespace description and transfer function;
 Analyse the stability of a feedback loop via frequency response as well as algebraic methods;
 Synthesise controllers based on manual as well as automated (optimizationbased) loopshaping;
 Identify and handle fundamental design tradeoffs and limitations in feedback controller synthesis;
 Discretise and implement a controller in computer and simulate the overall system behaviour;
 Determine the reachability and observability of a linear statespace model and synthesize an observerbased controller based on the separation theorem;
 Analyse the stability of a (nonlinear) system based on Lyapunov’s theorem, LaSalle’s invariance principle and passivity theorem;
 Synthesise a controller for a nonlinear robotic system in joint space as well as in operation space.
 Consider legal aspects in control design for autonomous robots (for MSc Robotics students)



Short description of course content:
 Linearization and statespace models, transfer function and frequency response, feedback and feedforward, decoupling, loop gain and sensitivities, characteristic polynomial and internal stability, Bode and Nyquist stability criterions, stability margins, loopshaping, mixedsensitivity synthesis, waterbed effect and bandwidth limitations.
 Reachability and observability of a statespace model, pole placement, linearquadratic regulator, Kalman filter, separation principle and observerbased controller synthesis.
 Lyapunov stability theory, LaSalle’s invariance principle, passivity and smallgain theorems, inverse dynamics compensation, feedback linearization, computed torque control, control in joint space and operation space.
 Sampling and discretization, sampling rate selection, computer implementation and simulation.
 Legal aspects of autonomous robots (for MSc Robotics students)
Instructional modes
The course is taught with the following teaching methods:
 Lectures (about 16 lectures (32h) of frontal teaching in block 1B).
 Tutorials (about 9 tutorial (18h) of tutorials in block 1B).
Students can contact the teacher for any questions through Canvas and by prescheduling meetings.
Assessment
The learning objectives are assessed as follows:
 Weekly assignments (40% of the total score) The weekly assignments partly prepare for the project assignment
 Project assignment (20% of the total score) The project contributes to the Challenge Based Learning portfolio for MScRobotics students.
 Written exam (40% of the total score)




 Assumed previous knowledgeMandatory basic knowledge on differential equations, classical dynamical mechanical modelling, linear systems, Laplace and Fourier transforms, PID control.
This knowledge can be obtained through the following UT Bachelor Modules: • ME module Mechatronics (201700128) • EE module Systems and Control (201700145) • Minor Biorobotics (201800178) 
Master Biomedical Engineering 
Master Electrical Engineering 
Master Mechanical Engineering 
Master Systems and Control 
Master Interaction Technology 
  Required materialsBookFeedback Systems, K.J. Åström and R.M. Murray (freely available online)
ISBN:9781400828739 
 BookA Mathematical Introduction to Robotic Manipulation, R.M. Murray, Z. Li, S. Shankar Sastry (freely available online)
ISBN:9780849379819 

 Recommended materialsBookFeedback Control Theory, J.C. Doyle, B.A. Francis, A.R. Tannenbaum (freely available online)
ISBN:9780486469331 
 BookMultivariable Feedback Control – Analysis and Design, S. Skogestad, I. Postlethwaite (Chapters 1, 2, 3 available online)
ISBN: 9788126552672 
 BookModern Control Engineering, K. Ogata
ISBN: 9780136156734 
 BookLinear System Theory and Design, C. T. Chen, (available as ebook via UT library) ISBN: 9780195117783 

 Instructional modesTestsExam, Assignment


 