Nonlinear Systems and Chaos
Code  Completion  Credits  Range  Language 

B3M35NES  Z,ZK  6  2P+2C  Czech 
 Course guarantor:
 Sergej Čelikovský
 Lecturer:
 Sergej Čelikovský, Kristian HengsterMovric
 Tutor:
 Kristian HengsterMovric, Volodymyr Lynnyk
 Supervisor:
 Department of Control Engineering
 Synopsis:

The goal of this course is to introduce basics of the modern approaches to the theory and applications of nonlinear control. Fundamental difference when dealing with nonlinear systems control compared with linear case is that the state space approach prevails. Indeed, the frequency response approach is almost useless in nonlinear control. State space models are based mainly on ordinary differential equations, therefore, an introduction to solving these equations is part of the course. More importantly, the qualitative methods for ordinary differential equations will be presented, among them Lyapunov stability theory is crucial. More specifically, the focus will be on Lyapunov function method enabling to analyse stability of nonlinear systems, not only that of linear ones. Furthemore, stabilization desing methods will be studied in detail, among them the socalled control Lyapunov function concept and related backstepping method. Special stress will be, nevertheless, given by this course to introduce and study methods how to transform complex nonlinear models to simpler forms where more standard linear methods would be applicable. Such an approach is usually refered to as the socalled exact nonlinearity compensation. Contrary to the wellknown approximate linearization this method does not ignore nonlinearities but compensates them up to the best possible extent. The course introduces some interesting case studies as well, e.g. the planar vertical take off and landing plane („planar VTOL“), or a simple 2dimensional model of the walking robot.
 Requirements:

Prerequisites are: knowledge of basics of control theory (frequency response, feedback, stability, PID controllers, etc.), finishing advanced course on linear systems introducing notions like controllability, observability. Last but not least, a good knowledge ol linear algebra (eigenvalues, eigenvectors, equivalence of matrices, canonical forms of matrices, etc.) and of mathematical analysis (multivariable differential calculus, ordinary differential equations).
 Syllabus of lectures:

1. State space description of the nonlinear dynamical system. Specific nonlinear properties and typical nonlinear phenomena. Nonlinear control techniques outlook.
2. Stability of equilibrium points. Approximate linearization method and Lyapunov function method.
3. Invariant sets and LaSalle principle. Exponential stability. Analysis of additive perturbations influence on asymptotically and exponentially stable nonlinear systems.
4. Feedback stabilization using control Lyapunov function. Backstepping.
5. Control design using structural methods. Definition of system transformations using the state and input variables change.
6. Control design using structural methods. Exact feedback linearization. Zero dynamics and minimum phase property.
7. Structure of singleinput singleoutput systems. Exact feedback linearization, relative degree, partial and inputoutput linearization, zero dynamics computation and minimum phase property test. Examples.
8. Structure of multiinput multioutput systems. Vector relative degree, inputoutput linearization and decoupling, zero dynamics computation and minimum phase property test.
9. Structure of multiinput multioutput systems.. Examples, dynamical feedback, example of its application in the case study of the planar vertical takeoff and landing plane.
10. Further examples of the practical applications of the exact feedback linearization.
 Syllabus of tutorials:

1.Examples of natural and technological systems modelled using nonlinear systems. Comparision of the exact linearization and aproximate linearization based control designs.
2. Nonlinear dynamical systems stability analysis. Lyapunov function and LaSalle principle.
3. Lyapunovbased control and the backstepping.
4. Lie derivative and its computation.
5. Exact feedback linearization of singleinput singleoutput nonlinear dynamical systems.
6. Exact feedback linearization of multiinput multioutput nonlinear dynamical systems.
 Study Objective:
 Study materials:

H.K. Khalil, Nonlinear Control, Global Edition, PEARSON, 2015.
Available in library
 Note:
 Further information:
 https://moodle.fel.cvut.cz/courses/B3M35NES
 Timetable for winter semester 2024/2025:

06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri  Timetable for summer semester 2024/2025:
 Timetable is not available yet
 The course is a part of the following study plans:

 Cybernetics and Robotics  Systems and Control (compulsory course of the specialization)
 Cybernetics and Robotics  Robotics (compulsory elective course)
 Cybernetics and Robotics  Senzors and Instrumention (compulsory elective course)
 Cybernetics and Robotics  Aerospace Systems (compulsory elective course)
 Cybernetics and Robotics  Cybernetics and Robotics (compulsory elective course)
 Cybernetics and Robotics (compulsory elective course)