352-0910/05 – Optimization (O)
Gurantor department | Department of Control Systems and Instrumentation | Credits | 10 |
Subject guarantor | prof. Ing. Miluše Vítečková, CSc. | Subject version guarantor | prof. Ing. Miluše Vítečková, CSc. |
Study level | postgraduate | Requirement | Choice-compulsory type B |
Year | | Semester | winter + summer |
| | Study language | English |
Year of introduction | 2014/2015 | Year of cancellation | |
Intended for the faculties | FS, HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Optimality criteria, conditions for optimality, constrains, forms of solution. The analytical and numerical methods of minimization of functions of single and several variables, equality constrains, inequality constrains, Kuhn-Tucker conditions, saddle point conditions. Minimization of functionals, optimal control problems. Bellman’s principle of optimality and dynamic programming. Pontryagin’s minimum principle. Calculus of variations. The method of ag-gregation of state variables in optimal control.
Teaching methods
Individual consultations
Project work
Summary
Optimality criteria, conditions for optimality, constrains, forms of solution. The analytical and numerical methods of minimization of functions of single and several variables, equality constrains, inequality constrains, Kuhn-Tucker conditions, saddle point conditions. Minimization of functionals, optimal control problems. Bellman’s principle of optimality and dynamic programming. Pontryagin’s minimum principle. Calculus of variations. The method of aggregation of state variables in optimal control.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Kontrola zadaného projektu.
E-learning
Other requirements
Elaboration of the project.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Static optimization. Optimization without constraints, optimization with constraints, numerical solution methods. Optimal control of discrete-time systems. Discrete-time linear quadratic regulator, Bellman’s principle of optimality, dynamic programming in discrete-time optimal control. Optimal control of continuous-time systems. Dynamic programming in continuous-time optimal control. Pontryagin minimum principle, calculus of variations. Aggregation method in optimal control. Standard systems, non-robust and robust control.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.