H. Rake

Binary Multifrequency Signals - Synthesis and Application

Abstract Methods for the identification of processes by using binary multifrequency test signals are presented. These periodic signals are used to determine the frequency response function of the process at preselected frequencies. The presentation includes improved methods for synthesis of signals leading to short measuring times, a formula for estimating the variance of frequency response values that uses available data and descriptions of results obtained by applying these test signals to simulated and to real processes.

Simultane Regelung von Ladedruck und AGR-Rate beim Pkw-Dieselmotor

In diesem Beitrag wird ein modellgestutzter pradiktiver Regler vorgestellt, der es ermoglicht, Ladedruck und AGR-Rate an einem Dieselmotor simultan zu regeln. Das Verfahren wurde vom Lehrstuhl fur Verbrennungskraftmaschinen Aachen (VKA) und dem Institut fur Regelungstechnik (IR) der RWTH Aachen in der Simulation entwickelt und an einem Prufstandsmotor erprobt. Neben der simultanen Regelung wird auch die Moglichkeit aufgezeigt, zum Beispiel unterschiedliche Wichtungen der Regelgrosen, virtuelle Sensoren oder auch weitere Regelgrosen unmittelbar in das Konzept zu integrieren.

Identification of Nonlinear Systems with Reduced Volterra-series

Abstract Volterra-series are very suitable for modelling nonlinear processes, since they cover a large class of nonlinear systems. In the past, it has often been pointed out that Volterra-series are not ideal for identification due to the large number of parameters, which have to be estimated. In this paper, a new identification method will be presented which reduces the number of estimated parameters to a reasonable size by introducing basis functions. Further reduction can be achieved using a selection algorithm, which selects the most suitable basis functions from a large class of different basis functions. In simulation examples, it will be shown that many nonlinear systems can be identified with less than 20 parameters.

Automation of a laboratory plant for direct casting of thin steel strips

Abstract The automation of a double roller laboratory plant for continuous casting of thin steel strip is described. A nonlinear state-space process model which represents the dynamics of the solidification and forming process has been developed. Based on this model the control concept using the force as the controlled variable has been derived and applied to the plant. Furthermore, starting the process which is difficult to handle is treated as an optimization problem. The solution to this task is given as a nonlinear two-point boundary value problem which is solved by means of a gradient method. A multi-microcomputer system based on the AMS-Bus has been developed to handle the variety of all tasks of automation at the laboratory plant.

MODEL-BASED BOOST PRESSURE AND EXHAUST GAS RECIRCULATION RATE CONTROL FOR A DIESEL ENGINE WITH VARIABLE TURBINE GEOMETRY

Abstract This paper presents two approaches of model-based control design for a coordinatedcontrol of boost pressure by a turbocharger with variable turbine geometry and of exhaust gas recirculation rate (EGR). One approach is an extension of conventional control structures of current car engine control units. The other one is a model-based predictive controller (MPC). A non-linear simulation model of the diesel engine was used for the controller design and compared with the test bench.

Step Response and Frequency Response Methods

Abstract In this tutorial very simple methods will be presented by which models for dynamic processes can be obtained. These methods employ step responses of the process or responses to other nonperiodic testsignals or process responses to periodic signals.

Nonlinear Model Predictive Control Based on Stable Wiener and Hammerstein Models

The presented Nonlinear Model Predictive Control (NMPC) scheme based on stable Wiener and Hammerstein models retains the characteristics of conventional linear Model Predictive Control (MPC) including capabilities to control stable nonlinear processes. The future process behavior is predicted by the q-th degree Wiener and Hammerstein model represented by Volterra-series. The optimal manipulated variable is calculated minimizing a quadratic cost function depending on the nonlinear predictor subject to input and output constraints.

Mechatronics in medical engineering: advanced control of a ventilation device

Abstract A typical mechatronics system consists of a mechanical process, electromechanical actuators, electronic sensors and a controller unit with the corresponding software. In this paper a microcontroller-based digital feedback control of a positioning device for a ventilation machine is presented. This kind of machine should allow either a volume- or a pressure-based controlled ventilation. The interdependence between the two important physiological variables, respiration volume and lung pressure, is highlighted and the requirements on the control system are discussed. Based on a mathematical model for the respiration device and the characteristics of the patients lung a feedback control concept for both respiration modes has been developed and is presented in this paper. By means of simulations the control concept has been tested. To sum up some simulation and experimental results are shown.

Online control of penetration depth in laser beam welding

In laser beam welding, the penetration depth is one of the most important quality aspects. Many industrial applications demand for accurate welding depths without fluctuations. As a consequence, the utilization of appropriate methods for online supervision and control of the welding depth is required. The development of a multivariable online control system for the control of the penetration depth in laser beam welding is described. The technical realization and the achieved results are figured out in detail. Comparison between controlled and uncontrolled laser welding shows the improvement. The control system is part of a higher ranked setup for controlling the whole manufacturing process within an autonomous production cell.

Gain Scheduled PI-Control of Strip Casting Plant

Abstract The controller design for a double roller laboratory plant for continuous casting of thin steel strip is described. A nonlinear state-space model which represents the dynamics of the solidification and forming process has been developed. Based on this model the control concept using the force as the controlled variable has been derived. Variations in static and dynamic behaviour depending on the actual operating point are compensated by gain scheduling PI-controller parameters.