Closed and Open Loop Subspace System Identification of the Kalman Filter

Some methods for consistent closed loop subspace system identification presented in the literature are analyzed and compared to a recently published subspace algorithm for both open as well as for closed loop data, the DSR_e algorithm. Some new variants of this algorithm are presented and discussed. Simulation experiments are included in order to illustrate if the algorithms are variance efficient or not

Dynamic system calibration by system identification methods

Primary output variables from industrial processes can be estimated from known input variables and secondary process measurements. As a basis for this, the dynamic predictor has to be identi ed from data collected during a calibration experiment. In this paper, the theoretical basis for this is investigated, and a systematic experimental method is proposed

Modeling, Identification and Control at Telemark University College

Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics

A Novel Process-Reaction Curve Method for Tuning PID Controllers

A novel process-reaction curve method for tuning PID controllers for (possible) higher order processes/models is presented. The proposed method is similar to the Ziegler-Nichols process reaction curve method, viz. only the maximum slope and lag need to be identified from an open loop step response. The relative time delay error (relative delay margin), delta is the tuning parameter. The proposed method is verified through extensive numerical simulations and is found close to optimal in many of the motivated process examples. In order to handle the wide set of process models, two model reduction modes are presented

Estimation, system identification and chemometrics

In our master degree program in process automation, traditional modeling and control courses are supplemented by courses in experimental design and chemometrics. A corresponding inter-disciplinary research program supports this innovation in curricular structure. The background for all this is the recent developments in chemometrics and the strong stand this discipline has in the Scandinavian process engineering and industrial communities. The program curriculum and related research results are presented, together with a summary of student and industrial feedback