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—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 non-linear in measured data and linear in unmeasured states. We present numerical simulations to demonstrate the efficacy of the method. 1(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. 1. Introduction Positive real transfer functions are of practical importance , arising in many(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)
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)
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)