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Journals and Conferences
In system identification, the true system is often known to be stable. However, due to finite sample constraints, modeling errors, plant disturbances and measurement noise, the identified model may be unstable. We present a constrained optimization method to ensure asymptotic stability of the identified model in the context of subspace identification… (More)
Wiener systems consist of a linear dynamic system whose output is measured through a static non-linearity. In this paper we study the identification of single-input single-output Wiener systems with finite impulse response dynamics and polynomial output non-linearities. Using multi-index notation, we solve a least squares problem to estimate products of the… (More)
In this paper we apply subspace methods to the identification of a class of multi-input multi-output discrete-time nonlinear time-varying systems. Specifically, we study the identification of systems that are nonlinear in measured data and linear in unmeasured states. We present numerical simulations to demonstrate the efficacy of the method.
Systems characterized by light damping present a challenging control problem and thus an important system identification problem. Large lightly damped structures are particularly prominent within the aerospace community, specifically large flexible space structures. This class of structures includes satellites, membranes, and other gossamer structures .… (More)
Seth L. Lacy Air Force Research Lab, Space Vehicles Kirtland AFB NM 87117 firstname.lastname@example.org Dennis S. Bernstein Aerospace Engineering, University of Michigan Ann Arbor MI 48109 email@example.com Abstract Limit cycle oscillations occur in a wide range of electrical, mechanical, and aerospace applications. In this paper we present a method for… (More)
This paper shows that the transfer function of a continuous-time positive real system with first-order-hold sampling is discrete-time positive real. Next, a method for identifying models that are constrained to be discretrtime positive real is developed.
Mathematical models describe the dynamic behavior of a system as a function of time, and arise in all scientific disciplines. These mathematical models are used for simulation, operator training, analysis, monitoring, fault detection, prediction, optimization, control system designs and quality control. System identification is the process of constructing… (More)
In this paper we develop a method for identifying SISO Wiener-type nonlinear systems, that is, systems consisting of a linear dynamic system followed by a static nonlinearity. Unlike previous techniques developed for Wiener system identification, our approach allows the identification of systems with nonlinearities that are known but not necessarily… (More)
System identification is the process of constructing models based on measured data. These identified models can then be used for controller and observer design, system analysis, and output prediction. Linear system identification has been well studied (Moonen et al. 1989, Söderstrom and Stoica 1989, Juang 1993, Van Overschee and De Moor 1996, Larimore… (More)
A b s t r a c t Hysteresis is usually characterized as a memorydependent relationship between inputs and outputs. While various operator models have been proposed, it is often convenient for engineering applications to approximate hysteretic behavior by means of finite-dimensional differential models. In the present paper we show that step-convergent… (More)