Dirk Söffker

State estimation of dynamical systems with nonlinearities by using proportional-integral observer

In this paper the application of a PI observer technique to dynamical systems with nonlinearities is proposed. The PI observer has two feedback loops, a proportional loop and an integral loop of the estimation error. In this way the PI observer combines the structures of the practical orientated nonlinearity observer developed by the third author and the classical Luenberger observer. The structure and the estimation performance of the PI observer are discussed and analysed. The results show that the PI observer can estimate the states not only of linear systems, but also, more significantly, of systems with any arbitrary external input which appear as unknown input, nonlinearity or unmodelled dynamics. It is shown that the PI observer works with weak assumptions, which can be fulfilled by many classes of systems to be observed. Owing to the weak assumptions it can improve many observer-based technical solutions as diagnosis or control based on observers. In the paper the conditions are given and proved. ...

Chaotic motions and fault detection in a cracked rotor

Applying the theory of Lyapunov exponents for nonsmooth dynamical systems, chaotic motions and strange attractors are found in the case of a cracked rotor. To detect the crack and establish a clear relation between shaft cracks in turbo rotors and induced phenomena in vibrations measured in bearings, a model-based method is applied. Based on a fictitious model of the time behaviour of the nonlinearities, a state observer of an extended dynamical system is designed resulting in estimates of the nonlinear effects.

From Human–Machine-Interaction Modeling to New Concepts Constructing Autonomous Systems: A Phenomenological Engineering-Oriented Approach

Modeling of the Human–Machine-Interaction (HMI) gives ideas to transfer the developed modeling approach of human interaction with formalizable environments to technical systems, like mobile robots, to give them some kind of autonomy for interaction tasks. The important task of the proposed new kind of intelligent control is to respond autonomously and problem-equivalent to complex or unknown situations. This includes learning capabilities and a well organized dynamic memory. The contribution introduces into the developed Situation-Operator model as the texturing theoretical background, into the complete concept, and classifies the known control approaches in the developed system-theoretic view of control and interaction, with or without autonomy.

Interaction of intelligent and autonomous systems – part II: realization of cognitive technical systems

In this study, the application of a meta-modelling technique to structure complex environments is demonstrated with two examples. A special situation-operator model developed to model the human-machine-interaction is applied to automated supervision within the HMI context and to realize flexible and situated interaction of autonomous systems. A concept to automated monitoring of human operators is introduced to illustrate the structuring of complex environments as the first example. In the second example, this modelling technique is applied to a mobile robot to autonomously build and update a mental model of the interaction with the environment as an example of a cognitive technical system.

Active Flutter Suppression of a Nonlinear Aeroelastic System Using PI-Observer

In this paper a novel robust control is proposed for the purpose of active flutter suppression of a nonlinear 2-D wing-flap system in the incompressible flow field. The controller consists of an optimized robust stabilizer in the form of state feedback control and a Proportional-Integral Observer (PI-Observer). The optimized robust stabilizer is based on the former study about the time-domain robust stable criterion and obtained by a numerical optimization process. The PI-Observer is taken to estimate not only the system states but the bounds of the nonlinearities which are necessary for the constraints of the optimization process. The simulation results are given to show the performance of this control design approach in suppressing the flutter and the limit cycle oscillations.

Cooperative Arrival Management in Air Traffic Control - A Coloured Petri Net Model of Sequence Planning

A Coloured Petri Net model implemented in CPN Tools is presented which simulates a potential future arrival planning process in air traffic control. The planning process includes a cooperation between airborne and ground side in which the aircraft involved provide information e.g. with regard to their estimated earliest and latest times of arrival at the airport. This information is then used by a planning system on the ground to establish a favorable sequence in which aircraft will be led to the runway. The model has been built in order to acquire a better understanding of how the behavior of individual actors (i.e. aircraft) within the cooperation influences the outcome of the overall sequence planning process. A peculiarity of the CP-net from a modeling point of view lies in the fact that state space analysis is used repeatedly during each cycle of the planning process to generate and evaluate the potential solutions to the sequence planning problem. The results gained through queries on the state space are then re-fed into the simulation and analysis for the next planning cycle. The results from the model will in future be used to build realistic scenarios and assumptions on how different actors will interact with the system from a human factors point of view.

Optimization Strategy for PID-Controller Design of AMB Rotor Systems

Most industrial active magnetic bearings (AMBs) are controlled by proportional-integral-derivative (PID) controllers. Usually, a time-consuming iterative manual tuning procedure is required to design these PID controllers. In this contribution, we introduce the strategy, algorithms, and results from an AMB controller design, including optimization using a multiobjective genetic algorithm. We focus on the combination of frequency- and time-domain-based optimization, a strategy for the evaluation of fitness functions for complex PID-controller design, and a sensitivity-based parameter reduction for optimization. Two AMB system controller designs are considered and satisfactory results are obtained using the suggested optimization strategy. For validation purposes, the optimized controller design is experimentally implemented for the first AMB system, which contains a flexible test rotor supported by two AMBs. The maximal rotational speed of 15 000 r/min is achieved for the test rotor. A comparison between simulated and experimental results is presented.

Original articles: Variable high-gain disturbance observer design with online adaption of observer gains embedded in numerical integration

In this paper, a variable gain design approach for the high-gain disturbance observer, called Proportional-Integral-Observer (PI-Observer), is proposed to solve the problem of choosing suitable observer gains. The high-gain PI-Observer is successfully applied to estimate unknown inputs of systems together with the system states. It is known that reasonable estimations of unknown inputs can only be derived using high observer gains. On the other hand, extremely large gains will cause serious problems with respect to measurements noise and unmodeled dynamics. According to the analysis of the estimation quality regarding to the factors which influence the estimation results, the optimal level of observer gains is changing during the estimation, an online adaption for the observer gains is therefore developed. The designed PI-Observer, called Advanced PI-Observer (API-Observer), will use changing observer gains from the adaption algorithm, which is proved to give stable estimation error dynamics. Simulation results from an elastic beam example are shown to illustrate the implementation of the API-Observer.

RETRACTED ARTICLE: Cargo pendulation suppression of ship cranes with elastic booms

This article concerns modelling and controller design for elastic ship-mounted cranes with the Maryland Rigging. Three inputs are employed to control the vibrations in the plane of the boom; the luff angle is utilized to ensure the controllability of the elastic boom, and the total length of the upper cable in conjunction with the position of its lower suspension point are used to guarantee the controllability of the payload. The dynamic behaviour of the crane is described by a multi-model approach depending on the current values of the cable length and boom luff angle. Consequently, a variable-gain observer and a variable-gain controller are designed to control the vibrations of the crane; the numerical values of the gains are updated according to the current operating region, which is determined by a region finder. Simulation and experimental results show that the expressed control strategy performs well and has a significant effect in controlling the vibrations of the crane for different operating conditions and payload masses.

A Cognitive-Oriented Architecture to Realize Autonomous Behavior - Part I: Theoretical Background

This contribution summarizes the theoretical background of a cognitive-oriented architecture to build autonomous systems. A special situation-operator-model, developed to model the human-machine-interaction, is used to structure the reality and map this structuring to a mental model of the system to enable planning and learning. The presented architecture builds the framework for autonomous behavior, where the mental model of the system is maintained and refined by the cognitive functions. The learning capabilities of the system and the steps to realize the proposed architecture in general are illustrated.