—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)
This paper uses subspace methods to identify a class of multi-input multi-output discrete-time non-linear time-varying systems. Specifically, we identify systems that are non-linear in measured data and linear in unmeasured states. Numerical examples are presented to demonstrate the efficacy of the method.
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 non-linear in measured data and linear in unmeasured states. We present numerical simulations to demonstrate the efficacy of the method. 1… (More)
Limit cycle oscillations occur in a wide range of electrical, mechanical, and aerospace applications. In this paper we present a method for constructing system models that are able to reproduce a periodic signal as a limiting trajectory. Our approach is based on continuous-time modeling of a scalar nth-order system whose dynamics are represented as a map of… (More)
1 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)
Hysteresis is usually characterized as a memory-dependent relationship between inputs and outputs. While various operator models have been proposed, it is often convenient for engineering applications to approximate hys-teretic behavior by means of finite-dimensional differential models. In the present paper we show that step-convergent semistable systems… (More)
Active control of thermo-acoustic instabilities represents a significant challenge and opportunity for feedback control technology. In this paper, we experimentally apply ARMARKOV adaptive control to a ducted flame with a servovalve actuator. This approach requires an identified model of the transfer function from the control input (modulated air stream) to… (More)
— This paper presents a method for identifying discrete-time models with a lower bound on the identified modal frequencies. A frequency bound is imposed as a convex constraint for a weighted least squares optimization in subspace identification. We solve the convex optimization problem using existing linear programming techniques.