Výpočetní aspekty návrhu regulátoru a vyčíslení kvality

This work contributes to the activity in the Department of Adaptive Systems in Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic to develop a complete design algorithm for advanced controllers such as the LQG one and put them through to real applications. The task of controller tuning is to transform the user specified requirements into the values of the tuning parameters. The system knowledge is incomplete. The Bayesian estimation delivers the parameters not as known numbers but as their probability density function. The important contribution of this work is extending the tuning to the multiple input multiple output (MIMO) controllers, where multiple constraints on particular quantities are considered simultaneously