ASE-5056 Optimal and Robust Control with Matlab, 8 cr
Additional information
Suitable for postgraduate studies
Person responsible
Terho Jussila, Risto Ritala, Robert Piche
Lessons
Implementation 1: ASE-5056 2015-02
Study type | P1 | P2 | P3 | P4 | Summer |
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Requirements
Written exam (or a set of written sub-exams) plus a PC Exam plus 7 PC sessions (each of 120 minutes) plus a practical LAB of 2-3 hours.
Completion parts must belong to the same implementation
Learning Outcomes
After the course the student should be able to use Matlab, Simulink, Control System Toolbox and Symbolic Toolbox to design a H2/LQ (Linear Quadratic) and LQG (LQ Gaussian) control law for a LTI (Linear Time-Invariant) state space system, analyze robust stability of the overall system in both classical and modern ways; can propose implementations; can use Matlab and the toolboxes for both time domain modeling, simulation and various other analyses of various MIMO LTI systems, including nominal and robustness analyses; knows several quadratic performance indices and their properties; understands special features and challenges of MIMO control design; can use both state space and transfer function models in an appropriate way and make conversions between model types; can create simple Matlab tools when Toolboxes are not providing suitable ones.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Time domain simulation of various model types with Simulink, Control System Toolbox and tools of the core Matlab. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | S functions of Simulink. Creating and masking sub-systems. Use of ode45 and dde23. |
2. | Matlab and Control System Toolbox for effective modelling: equilibriums, linearization, least squares, model reduction, model type conversions, building models from sub-system models. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | Solvers and optimizers. |
3. | Basics of Linear Time Invariant models of MIMO systems: example responses, stability, controllability, observability, transfer function matrix, frequency response. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | |
4. | Quadratic performance indices and signal norms, even for time-delay systems and including time-weighting. Linear Quadratic deterministic state-feedback control and quadratic optimal parametric control. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | |
5. | Classical and modern studies of robust stability: stability margins for MIMO systems and studies of unstructured uncertainty. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | |
6. | Vector random processess in time and frequency domain. Identification, spectral factorization. Mean and variance calculus, variance minimization. Stochastic regulator, Kalman filtering, LQG control. | Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately. | |
7. | Improving reliability of the computations. |
Instructions for students on how to achieve the learning outcomes
Usual.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
Type | Name | Author | ISBN | URL | Additional information | Examination material |
Book | Nomen Nescio | The main course book will be specified separately for each particular implementation. | Yes | |||
Summary of lectures | Lecturer | The lecture notes/slides will be specified separately for each particular implementation. | Yes |
Prerequisites
Course | Mandatory/Advisable | Description |
ASE-1130 Automaatio | Mandatory | 1 |
ASE-1251 Järjestelmien ohjaus | Mandatory | 1 |
ASE-1257 Introduction to Control | Mandatory | 1 |
1 . One of the ASE courses 1130, 1251, 1257 is necessary if the student is not mastering the content of such a course otherwise.
Correspondence of content
Course | Corresponds course | Description |
ACI-21086 Control System Design with Matlab, 5 cr + ACI-42066 Robust Control, 5 cr + ASE-5056 Optimal and Robust Control with Matlab, 8 cr | ACI-42086 Optimal and Robust Control System Design with Matlab, 7 cr | |
ASE-5056 Optimal and Robust Control with Matlab, 8 cr | ASE-5056 Optimal and Robust Control with Matlab, 8 cr | |
ASE-5056 Optimal and Robust Control with Matlab, 8 cr | ACI-21086 Control System Design with Matlab, 5 cr |