When one wants to use Orthogonal Rational Functions (ORFs) in system identification or control theory, it is important to be able to avoid complex calculations. In this paper we study ORFs whose numerator and denominator polynomial have real coefficients. These ORFs with real coefficients (RORFs) appear when the poles and the interpolation points appear in complex conjugate pairs, which is a na...

We examine some recent methods for System Identification, that also deliver non-parametric error bounds, suited for a robust controller design. In particular, we look at Stochastic Embedding, Set Membership Identification and Model Error Modelling. We briefly review the main ideas together with existing computational solutions and present a comparative example.

The performance of robust controllers hinges on the underlyingmodel set. The aim of the present paper is to develop a system identification procedure that enables the design of a controller that achieves optimal robust performance. Hereto, the complex interrelation between system identification and robust control is thoroughly analyzed and novel connections are established between (i) control-r...

A new approach is given for the design of adaptive robust control in the frequency domain. Starting with an initial model of a stable plant and a robust stabilizing controller, the new (windsurfer) approach allows the bandwidth of the closed-loop system to he increased progressively through an iterative controlrelevant system identification and control design procedure. The method deals with bo...

In this paper a framework for connecting system identi cation and robust control design via a factorization approach is being introduced. Within the scope of this framework, models are represented in an estimated set of models that is used subsequently to design a robust performing controller. The set of models is structured by means of a nominal coprime factorization along with an allowable pe...

Various techniques of system identification exist providing for a nominal model and uncertainty bound. An important question is what the implications are for the particular choice of the structure in which the uncertainty is described when dealing with robust stability/performance analysis of a given controller and when dealing with robust synthesis. An amplitude-bounded (circular) uncertainty ...

OF THE DISSERTATION Exploratory studies of human sensorimotor learning with system identification and stochastic optimal control

In mobile robotics, it is common to find different control programs designed to achieve a particular robot task. It is often necessary to compare the performance of such controllers. So far this is usually done qualitatively, because of a lack of quantitative behaviour analysis methods. In this paper we present a novel approach to compare robot control codes quantitatively, based on system iden...

A new Modular Recurrent Trainable Neural Network (MRTNN) has been used for system identification of two-mass-resort-damper nonlinear oscillatory plant. The first MRTNN module identified the exponential part of the unknown plant and the second one the oscillatory part of the plant. The plant has been controlled by a direct adaptive neural control system with integral term. The RTNN controller us...

Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour based on theoretical models. Instead, current methods to develop robot control code ...