Closed-loop pole

About: Closed-loop pole is a research topic. Over the lifetime, 886 publications have been published within this topic receiving 13621 citations.

Poles, zeros, and feedback: State space interpretation

Abstract: This paper is concerned with the relationships between time and frequency domain descriptions of linear, time-invariant systems and with the evaluation of the effects of feedback on such systems A new expression for the transfer function of a system described by a set of first-order differential equations is given; this expression not only relates the poles and zeros to the eigenvalues of matrices but also makes it possible to compute the transfer function without matrix inversion The effects of state variable feedback on controllability, observability, and pole-zero configurations are discussed and the effects of feeding back the output and its derivatives are considered The application of these ideas to an optimal control problem is sketched and methods of extending them to the multi-input, multi-output case are examined

Asymptotic properties of black-box identification of transfer functions

Abstract: The problem of estimating the transfer function of a linear, stochastic system is considered. The transfer function is parametrized as a black box and no given order is chosen a priori. This means that the model orders may increase to infinity when the number of observed data tends to infinity. The consistency and convergence properties of the resulting transfer function estimates are investigated. Asymptotic expressions for the variances and distributions of these estimates are also derived for the case that the model orders increase. It is shown that the variance of the transfer function estimate at a certain frequency is asymptotically given by the noise-to-signal ratio at that frequency mulliplied by the model-order-to-number-of-data-points ratio.

Model matching by state feedback and dynamic compensation

Abstract: A new approach to the exact model matching problem is given based on an algorithm for characterizing the input-output structural properties of a linear system. In contrast to previous methods, the state feedback matching problem is solved without recourse to initial coordinate transformations. Moreover, the algorithm given here extends directly to the dynamic model matching problem and yields a set of necessary and sufficient conditions for one system to be transfer function equivalent via dynamic state feedback to a specified model system.

Experimental evaluation of STATCOM closed loop dynamics

Abstract: This paper presents a new approach for the dynamic control of FACTS apparatus, such as the STATCOM and UPFC, which utilize voltage source inverters (VSI) as their main building block. The control concept is based on a linearization of the dq inverter model. Feedforward techniques which are traditionally used for the approximate decoupling of d and q-axis control are discarded, in favour of a high gain full state feedback approach which assigns both closed loop system poles and, more importantly, their associated eigenvectors. Experimental validation of the approach is carried out on a laboratory STATCOM setup. Due to the nonlinear nature of the VSI equations and the uncertainty of AC system parameters, actual closed loop system dynamics can stray quite dramatically from those desired. Root locus analysis is therefore performed to investigate the small signal system dynamic behaviour. The loci demonstrate that the effect of system nonlinearity on the closed loop poles is virtually eliminated by the proposed control. The effect of AC system parameter variations is also shown to be minimal.

Adaptive control of nonminimum phase systems

Abstract: Recent papers have established global convergence for a class of adaptive control algorithms for discrete time linear dynamic systems. However, in most cases studied to date it has been assumed that the system is stably invertible. This assumption plays a major role in the proofs of convergence. In this paper we consider the more general case in which it is not assumed that the system is either stable or stably invertible. We establish local convergence for a class of adaptive control algorithms applied to general discrete, deterministic, linear, time-invariant systems. By convergence in this context, we mean that the system inputs and outputs remain bounded for all time and the closed loop poles are effectively assigned in the limit for a given desired trajectory.