4,177 research outputs found
Robust Asymptotic Stabilization of Nonlinear Systems with Non-Hyperbolic Zero Dynamics
In this paper we present a general tool to handle the presence of zero
dynamics which are asymptotically but not locally exponentially stable in
problems of robust nonlinear stabilization by output feedback. We show how it
is possible to design locally Lipschitz stabilizers under conditions which only
rely upon a partial detectability assumption on the controlled plant, by
obtaining a robust stabilizing paradigm which is not based on design of
observers and separation principles. The main design idea comes from recent
achievements in the field of output regulation and specifically in the design
of nonlinear internal models.Comment: 30 pages. Preliminary versions accepted at the 47th IEEE Conference
on Decision and Control, 200
Parameter estimation in kinetic reaction models using nonlinear observers facilitated by model extensions
An essential part of mathematical modelling is the accurate and reliable estimation of model parameters. In biology, the required parameters are particularly difficult to measure due to either shortcomings of the measurement technology or a lack of direct measurements. In both cases, parameters must be estimated from indirect measurements, usually in the form of time-series data. Here, we present a novel approach for parameter estimation that is particularly tailored to biological models consisting of nonlinear ordinary differential equations. By assuming specific types of nonlinearities common in biology, resulting from generalised mass action, Hill kinetics and products thereof, we can take a three step approach: (1) transform the identification into an observer problem using a suitable model extension that decouples the estimation of non-measured states from the parameters; (2) reconstruct all extended states using suitable nonlinear observers; (3) estimate the parameters using the reconstructed states. The actual estimation of the parameters is based on the intrinsic dependencies of the extended states arising from the definitions of the extended variables. An important advantage of the proposed method is that it allows to identify suitable measurements and/or model structures for which the parameters can be estimated. Furthermore, the proposed identification approach is generally applicable to models of metabolic networks, signal transduction and gene regulation
Local weak observability conditions of sensorless AC drives
Alternating current (AC) electrical drive control without mechanical sensors
is an active research topic. This paper studies the observability of both
induction machine and synchronous machine sensorless drives. Observer-based
sensorless techniques are known for their deteriorated performance in some
operating conditions. An observability analysis of the machines helps
understanding (and improving) the observer's behavior in the aforementioned
conditions.Comment: arXiv admin note: text overlap with arXiv:1512.0366
Observability analysis of sensorless synchronous machine drives
This paper studies the local observability of synchronous machines using a
unified approach. Recently, motion sensorless control of electrical drives has
gained high interest. The main challenge for such a technology is the poor
performance in some operation conditions. One interesting theory that helps
understanding the origin of this problem is the observability analysis of
nonlinear systems. In this paper, the observability of the wound-rotor
synchronous machine is studied. The results are extended to other synchronous
machines, adopting a unified analysis. Furthermore, a high-frequency
injection-based technique is proposed to enhance the sensorless operation of
the wound-rotor synchronous machine at standstill
A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems
This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version
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