Admissible target paths in economic models

Social Psychology;econometrics

Output feedback control and robustness in the gap metric

Zusammenfassung Mueller, Markus: Output feedback control and robustness in the gap metric Ilmenau : Univ.-Verl. Ilmenau, 2009. - 254 S. ISBN 978-3-939473-60-2 Die vorgelegte Arbeit behandelt den Entwurf und die Robustheit von drei verschiedenen Regelstrategien für lineare Differentialgleichungssysteme mit mehrdimensionalen Ein- und Ausgangssignalen (MIMO): Stabilisierung durch Ausgangs-Ableitungs-Rückführung, Lambda-tracking und Funnel-Regelung. Damit diese Regler bei der Anwendung auf ein lineares System die gewünschten Stabilisierung/Regelung erbringen, ist eine explizite Kenntnis der Systemmatrizen nicht notwendig. Es müssen nur strukturelle Eigenschaften des Systems bekannt sein: der Relativgrad, dass das System minimalphasig ist, und dass die sogenannte "high-frequency gain" Matrix positiv definit ist. Diese stukturellen Eigenschaften werden für MIMO-Systeme in den ersten Kapiteln der Arbeit ausführlich behandelt. Für MIMO-Systeme mit nicht striktem Relativgrad wird eine Normalform hergeleitet, die die gleichen Eigenschaften wie die bekannte Normalform für SISO-Systeme oder MIMO-Systeme mit striktem Relativgrad aufweist. Die Normalform sowie Minimalphasigkeit und Positivität der "high-frequency gain" Matrix bilden die Grundlage dafür, dass die oben genannten Regelstrategien Systeme mit diesen Eigenschaften im jeweiligen Sinn stabilisieren. Robustheit bzw. robuste Stabilisierung beschreibt folgendes Prinzip: falls ein geschlossener Kreis aus einem linearen System und einem Regler in gewissem Sinne stabil ist und die Gap-Metrik (der Abstand) zwischen dem im geschlossenen Kreis betrachteten System und einem anderen "neuen" System hinreichend klein ist, so ist der geschlossene Kreis aus dem "neuen" System und dem gleichen Regler wieder stabil. Die gleiche Aussage stimmt auch für den Fall, dass man den Regler und nicht das System austauscht. Für Ausgangs-Ableitungs-Rückführung wird gezeigt, dass, falls diese ein System stabilisiert, die auftretenden Ableitungen des Ausgangs durch Euler-Approximationen der Ableitungen ersetzt werden können, falls diese hinreichend genau sind. Für Lambda-tracking und Funnel-Regelung wird gezeigt, dass beide Regler auch für die Stabilisierung linearer Systeme verwendet werden können, die einen geringen Abstand zu einem System haben, dass die o.g. Voraussetzungen erfüllt, selbst diese Voraussetzungen aber nicht erfüllen.Abstract: This dissertation considers the design and robustness analysis of three different control strategies for linear systems of differential equations with multidimensional input and output signals (MIMO): high-gain output derivative feedback control, lambda-tracking and funnel control. To apply these control strategies to linear systems and achieve the desired control objectives (stabilization or tracking), the explicit system's data needs not to be known, but certain structural properties of the systems are required. The system's relative degree must be known, the system must be minimum phase and the so-called "high-frequency gain" matrix must be positive definite. These properties are considered in detail for linear MIMO-systems with non-strict relative degree. A normal form is developed which has the same properties as the well-known normal form for SISO-systems or MIMO-systems with strict relative degree. Normal form, minimum phase property and positivity of the high-frequency gain matrix are the crucial assumptions for the application of the control strategies mentioned above. It is shown that each controller achieves certain control objectives when applied to any system which satisfies these assumptions. The result on robustness and robust stability are as follows: if a closed-loop system represented by the application of a controller to a linear plant is stable (in some sense), and the gap metric (i.e. the distance) between the stabilised system and a different "new" system is sufficiently small, then the closed-loop system represented by the application of the controller to the "new" system is again stable. This conclusion holds also true when changing the roles of system and controller. For high-gain output derivative feedback control it is shown that the controller still stabilizes a system when the derivatives of the output are replaced by Euler approximations of the derivatives, provided the approximation is sufficiently precise. For lambda-tracking and funnel control it is shown that both controllers may be applied to systems which are "close" (in terms of a small gap) to any system from the class of minimum phase systems, with relative degree one and positive definite high-frequency gain matrix, but not necessarily satisfy any of these assumptions

A Predictive Fuzzy-Neural Autopilot for the Guidance of Small Motorised Marine Craft

This thesis investigates the design and evaluation of a control system, that is able to adapt quickly to changes in environment and steering characteristics. This type of controller is particularly suited for applications with wide-ranging working conditions such as those experienced by small motorised craft. A small motorised craft is assumed to be highly agile and prone to disturbances, being thrown off-course very easily when travelling at high speed 'but rather heavy and sluggish at low speeds. Unlike large vessels, the steering characteristics of the craft will change tremendously with a change in forward speed. Any new design of autopilot needs to be to compensate for these changes in dynamic characteristics to maintain near optimal levels of performance. This study identities the problems that need to be overcome and the variables involved. A self-organising fuzzy logic controller is developed and tested in simulation. This type of controller learns on-line but has certain performance limitations. The major original contribution of this research investigation is the development of an improved self-adaptive and predictive control concept, the Predictive Self-organising Fuzzy Logic Controller (PSoFLC). The novel feature of the control algorithm is that is uses a neural network as a predictive simulator of the boat's future response and this network is then incorporated into the control loop to improve the course changing, as well as course keeping capabilities of the autopilot investigated. The autopilot is tested in simulation to validate the working principle of the concept and to demonstrate the self-tuning of the control parameters. Further work is required to establish the suitability of the proposed novel concept to other control

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties