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- model reduction (4)
- balanced truncation (3)
- differential-algebraic equations (2)
- funnel control (2)
- high-gain output feedback (2)
- minimum phase (2)
- stabilization (2)
- strict relative degree (2)
- zero dynamics (2)
- Coupled systems (1)
In this paper we consider structure-preserving model reduction of
second-order systems using a~ba\-lan\-ced truncation approach.
Several sets of singular values are introduced for such systems,
which lead to different concepts of balancing and different
second-order balanced truncation methods. We compare the
properties of these methods on numerical examples.
In this paper we give an overview of model
order reduction techniques for coupled
systems. We consider linear time-invariant
control systems that are coupled through
input-output relations and discuss model
reduction of such systems using moment
matching and balanced truncation.
Structure-preserving approaches to model
order reduction of coupled systems are also
presented. Numerical examples are given.
Consistent Initialization and Perturbation Analysis for Abstract Differential-Algebraic Equations
(2006)
In this paper we consider linear and time-invariant
differential-algebraic equations (DAEs) $E\dot{x}(t)=Ax(t)+f(t)$,
$x(0)=x_0$, where $x(\cdot)$ and $f(\cdot)$ are functions with
values in separable Hilbert spaces $X$ and $Z$. $E:X\To Z$ is
assumed to be a bounded operator, whereas $A$ is closed and defined
on some dense subspace $D(A)$ which is in general a proper subset of
$X$. Based on a decoupling of the algebraic and the differential
part, the set of initial values being consistent with the given
inhomogeneity will be parameterized. As a consequence of these results, we
will derive estimates for the trajectory $x(\cdot)$ in dependence of the initial
state $x_0$ and the inhomogeneity $f(\cdot)$. In the theory of
differential-algebraic equations, this is commonly known as
perturbation analysis.
We propose a model reduction method for positive systems that ensures the positivity of the reduced-order model. In the standard as well as in the descriptor case, for continuous-time and discrete-time systems, our approach is based on constructing diagonal solutions of Lyapunov inequalities. These are linear matrix inequalities (LMIs), which are shown to be feasible. Positivity and stability are preserved and an error bound in the $\mathcal{H}_\infty$-norm is provided.
We study the class of linear differential-algebraic m-input m-output systems
which have a transfer function with proper inverse.
A sufficient condition for the transfer function to have proper inverse
it that the system has 'strict and non-positive relative degree'.
We present two main results:
First, a so called 'zero dynamics form' is derived: this form is - within the class of system equivalence - a simple "almost normal" form of the DAE; it is a counterpart to the well-known Byrnes-Isidori form for
ODE systems with strictly proper transfer function.
The 'zero dynamics form' is exploited to characterize structural properties such as
asymptotically stable zero dynamics,
minimum phase, and high-gain stabilizability.
The zero dynamics are characterized by (A,E,B)-invariant subspaces.
Secondly, it is shown that the 'funnel controller' (that is a static nonlinear output error feedback) achieves, for all DAE systems with asymptotically stable zero dynamics and transfer function with proper inverse, tracking of a reference signal by the output signal within a pre-specified funnel. This funnel determines the transient behaviour.
Model Reduction for a Class of Nonlinear Electrical Circuits by Reduction of Linear Subcircuits
(2010)
We analyze a model reduction approach for a class of electrical circuits containing nonlinear resistance.
In our approach
the linear subcircuits are extracted and replaced with linear passive reduced-order models. The resulting nonlinear
reduced-order model preserves admissibility and passivity. Moreover, we derive a-priori bounds for the error between
the input-output map of the original circuit equations and that of our reduced-order model. These bounds
are valid for all inputs. Since only linear subcircuits are reduced, our approach is effective when the number of nonlinear resistances is relatively small. The performance of our approach is illustrated numerically.
In this work we consider the so-called Lur'e matrix equations that arise e.g. in model reduction and linear-quadratic infinite time horizon optimal control. We characterize the set of solutions in terms of deflating subspaces of even matrix pencils. In particular, it is shown that there exist solutions which are extremal in terms of definiteness. It is shown how these special solutions can be constructed deflating subspaces of even matrix pencils.
We introduce a~numerical method for the numerical solution of the Lur'e matrix equations that arise, for instance, in linear-quadratic infinite time horizon optimal control. The method is based on the characterization of the solutions in terms of deflating subspaces of a suitable even matrix pencil. Via a Cayley transformation, the problem is transformed to the discrete-time case. This leaves us with a symplectic problem with several Jordan blocks of eigenvalue 1 and even size, which arise from the remaining eigenvalues at infinity of the original problem. For the solution of this modified problem, we use the {\em structure-preserving doubling algorithm} (SDA), an iterative scheme for the solution of dense continuous- and discrete-time algebraic Riccati equations. Unlike other iterative schemes, this algorithm converges also when the pencil has eigenvalues on the unit circle, as is the case in our problem. Implementation issues such as the choice of the parameter $\gamma$ in the Cayley transform are discussed. The numerical examples presented confirm the effectiveness of this method.
We consider linear differential-algebraic m-input m-output systems with positive
strict relative degree or proper inverse transfer function; in the single-input single-output case these
two disjoint classes make the whole of all linear DAEs without feedthrough term. Structural properties
- such as normal forms (i.e. the counterpart to the Byrnes-Isidori form for ODE systems), zero
dynamics, and high-gain stabilizability - are analyzed for two purposes: first, to gain insight into the
system classes and secondly, to solve the output regulation problem by funnel control. The funnel
controller achieves tracking of a class of reference signals within a pre-specified funnel; this means in
particular, the transient behaviour of the output error can be specified and the funnel controller does
neither incorporate any internal model for the reference signals nor any identification mechanism, it
is simple in its design. The results are illuminated by position and velocity control of a mechanical
system encompassing springs, masses, and dampers.