| Objectives |
Identification of beneficial properties of convex optimization problems, basic knowledge about linear and semidefinite programming, the ability to formulate control problems as linear or semidefinite programs and to solve them numerically by appropriate algorithms, understanding the principles of variational calculus and its application to optimal control problems. Skills for the generation and numerical solution of convex parameter optimization tasks, experience in the formulation of practice-relevant tasks.
The level of the mathematical methods used to describe the dynamic systems, to design the control laws and to synthesize the control circuits corresponds roughly to that in the textbooks S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004; S. Boyd, L. El Gaoui, E. Feron, V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, SIAM Studies in Applied Mathematics, Vol. 15, 1994; A. E. Bryson, Yu-C. Ho, Applied Optimal Control, Hemisphere Publishing Corporation, 1975.
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| Subject |
Fundamentals of parameter optimization, convex optimization problems, introduction to linear programming, control system design based on linear programming methods, semidefinite programs, control system design by semidefinite programming, variational calculus, solution of optimal control problems by variational calculus, linear systems with quadratic objective function. Use of Matlab and YALMIP to generate and solve convex parameter optimization tasks, design of digital filters with linear programming.
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