Objectives of subject
The main objective is to continue deepening the fundamentals from Control System Theory I in time and frequency analysis. New aspects and mathematical approaches are revealed by the means of state space domain. Also, nonlinear systems analysis and synthesis methods are developed in the frequency domain and in the state-space. Fuzzy systems, neural and genetic systems are also studied to provide the student with a modern advanced view of systems theory.
Simulation, modeling and testing of nonlinear systems are meant to develop within dedicated environment like or using analog or digital equipments available in the special platform oriented lab.
Specific Competencies
Part I: Linear Systems
1. Introduction. Linear models
2. Linear systems. Root locus method
3. Linear systems. State space
3.1. State space representation of linear systems
3.2. Time domain analysis within state space
3.3. Controlability. Observability
3.4. Transfer function and state space representation
3.5. Controller design
Part II: Nonlinear systems
4. Nonlinear systems
4.1. Introduction
4.2. Continuous and discontinuous nonlinearities. Linearization
4.3. Describing function
4.4. Stability
4.5. Building structures of nonlinear systems. Analysis and design methodologies
Part III: Inteligent control systems
5. Fuzzy systems
5.1. Introduction
5.2. Fuzzy logic basics. Basic rules in fuzzy logic
5.3. Fuzzy systems
5.4. Fuzzy control
6. Neural Networks
6.1. Introduction
6.2. Neural networks basics
6.3. Multilayer structures. The Perceptron
6.4. Neural networks control
7. Evolutionary algorithms
7.1. Evolutionary strategies. Examples
7.2. Genetic algorithms. Examples
Afferent documents