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IEEE Conference on Decision and control

作者： Jie Chen C.N. Nett Georgia Institute of Technology Schools of Aerospace and Electrical Engineering Atlanta GA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems (LICCHUS) Georgia Institute of Technology School of Applied and Engineering Physics Atlanta GA USA

The purpose of this paper is to develop integral formulae for singular values of the sensitivity function to express design constraints in multivariable discrete-time systems. We present extensions to both the classical Poisson integral and Bode's sensitivity integral formulae. The main utility of these results is that they can be used to quantify design limitations that arise in multivariable discrete-time systems, due to such system characteristics as open loop unstable poles and nonminimum phase zeros, and to such design requirements as stability and bandwidth constraints. These formulae are similar to those for multivariable continuous-time systems obtained elsewhere, and they reveal that the limitations on the sensitivity design depend on directionality properties of the sensitivity function, as well as on those of unstable poles and nonminimum phase zeros in the open loop transfer function.< >

关键词： Matrix decomposition MIMO Harmonic analysis Singular value decomposition Laplace equations

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The Caratheodory-Fejer problem and H/sub /spl infin// identification: a time domain approach

The Caratheodory-Fejer problem and H/sub /spl infin// identi...

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IEEE Conference on Decision and control

作者： Jie Chen C.N. Nett Schools of Aerospace and Electrical Engineering Georgia Institute of Technology Atlanta GA USA Laboratory for Identification and Control of Complex Highly Uncertain System (LICCHUS) Schod d Aerospace Engineering Georgia Institute of Technology Atlanta GA USA

Addresses a worst-case, robust control oriented identification problem. This problem is a variant in the general framework of H/sub /spl infin// identification problems which have been studied by several authors. In this problem the available a priori information consists of a lower bound on the relative stability of the plant, an upper bound on a certain gain associated with the plant, and an upper bound on the noise level. The plant to be identified is assumed to lie in a certain subset in the space of H/sub /spl infin//. The available experimental information consists of a corrupt finite output time series obtained in response to a known nonzero but otherwise arbitrary input. The objective is to identify from the given a priori and experimental information an uncertain model which includes a nominal plant model in H/sub /spl infin// and a bound on the modeling error measured in H/sub /spl infin// norm. The authors present both an identification error and several explicit lower and upper bounds on the identification error. The proposed algorithm is in the class of interpolatory algorithms which are known to posses desirable optimality properties in reducing the identification error. This algorithm may be obtained by solving an extended Caratheodory-Fejer problem via standard convex programming methods. The error bounds not only provide explicit estimates on the modeling error, but also are used to establish the convergence properties of the proposed identification algorithm.< >

关键词： Robust control Upper bound Error correction Interpolation Stability Noise level Convergence System identification Frequency Approximation algorithms

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Worst Case identification of Continuous time systems via Interpolation

Worst Case Identification of Continuous time Systems via Int...

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American control Conference (ACC)

作者： Jie Chen Guoxiang Gu Carl N. Nett Schools of AeroSpace and Electrical Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Louisiana State University Baton Rouge LA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems(LIC-CHUS) School of Aerosapce Engineering Georgia Institute of Technology Atlanta GA USA

We consider a worse case control oriented identification problem recently studied by several authors. This problem is one of the H∞ identification in the continuous time setting. We give a less conservative formulation of this problem. The available apriori information consists of a lower bound on the relative stability of the plant, a frequency dependent upper bound on a certain gain associated with the plant, and an upper bound on the noise level. The available experimental information consists of a finite number of noisy plant point frequency response samples. The objective is to identify from the given apriori and experimental information an uncertain model that includes a stable nominal plant model and a bound on the modeling error measured in H∞ norm. Our main contributions include both a new identification algorithm and several new explicit lower and upper bounds on the identification error. The algorithm proposed belongs to the class of interpolatory algorithms which are known to possess a desirable optimality property under a certain criterion. The error bounds presented improve upon the previously available ones in both the aspects of providing a more accurate estimate of the identification error as well as establishing a faster convergence rate for the proposed algorithm.

关键词： Continuous time systems Interpolation Upper bound control systems Frequency Convergence Sampling methods Stability Noise level System identification

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Optimal Non-Parametric System identification From Arbitrary Corrupt Finite Time Series: A control-Oriented Approach

Optimal Non-Parametric System Identification From Arbitrary ...

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American control Conference (ACC)

作者： Jie Chen Carl N. Nett Michael K. H. Fan Schools of Aerospace and Electrical Engineering Georgia Institute of Technology Atlanta GA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems (LICCHUS) School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Computer-Aided Control Systems Engineering Laboratory (CACSEL) School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA

In this paper we formulate and solve a control-oriented system identification problem for single-input, single-output, linear, shift-invariant, distributed parameter plants. In this problem the available apriori information is minimal, consisting only of worst-case/deterministic, time dependent, upper and lower bounds on the plant impulse response and the additive output noise. The available aposteriori information consists of a corrupt finite output time series obtained in response to a known, non-zero but otherwise arbitrary, applied input. A novel system identification method is presented for this problem. This method maps the available apriori and aposteriori information into an "uncertain model" of the plant. The resulting uncertain plant model is comprised of a nominal plant model, a bounded additive output noise, and a bounded additive model uncertainty. The upper bound on the model uncertainty is explicit, worst-case/deterministic in nature, and expressed in terms of both the l 1 and H ∞ system norms. Under the assumption that the available apriori information is "correct" for the underlying physical plant, the resulting uncertain plant model has the property that it not only "explains" the available aposteriori information, but will also explain all aposteniori information observed in the future. Because this property hinges on the correctness of the available apriori information, a method is also presented for developing confidence that the available apriori information is in fact correct.

关键词： System identification Optimal control control systems Additive noise Robust control uncertainty Noise level Aerospace engineering Upper bound Fasteners

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Worst-case system identification in H∞: validation of apriori information, essentially optimal algorithms, and error bounds

Worst-case system identification in H∞: validation of aprio...

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American control Conference (ACC)

作者： Jie Chen Carl N. Nett Michael K.H. Fan Georgia Institute of Technology Schools of Aerospace and Electrical Engineering Atlanta GA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems (LICCHUS) Georgia Institute School of Applied and Engineering Physics USA School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA

This paper is concerned with a particular control-oriented system identification problem recently considered by several authors. This problem has been referred to as the problem of worst-case system identification in H ∞ in the literature. The formulation of this problem is worst-case/deterministic in nature. The available apriori information consists of a lower bound on the relative stability of the plant, an upper bound on a certain gain associated with the plant, and an upper bound on the noise level. The available aposteriori information consists-of a finite number of noisy plant point frequency response samples. The objective is to identify the plant transfer function in H ∞ using the available apriori and aposteriori information. In this paper we resolve several important open issues pertaining to this problem. First, a method is presented for developing confidence that the available apriori information is correct. This method requires the solution of a certain nondifferentiable convex programming problem. Second, an essentially optimal identification algorithm is given for this problem. This algorithm is (worst-case strongy) optimal to within a factor of two. Finally, new upper and lower bounds on the optimal identification error for this problem are derived and used to estimate the identification error associated with the algorithm presented here. Interestingly, the development of each of the results described above draws heavily upon the classical Nevanlinna-Pick optimal interpolation theory. As such, the results of this paper establish a clear link between the areas of system identification and optimal interpolation theory.

关键词： System identification Interpolation Upper bound Noise level control systems Stability Frequency response Aerospace engineering Space technology Transfer functions

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An Integrated Approach to controls and Diagnostics Using the Four Parameter controller

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IEEE control systems 1991年第6期11卷 22-29页

作者： Jacobson, C.A. Nett, C.N. Department of Electrical and Computer Engineering Northeastern University Boston MA 02115 United States School of Aerospace Engineering Laboratory for Identification Control of Complex Highly Uncertain Systems (LICCHUS) Georgia Institute of Technology Atlanta GA 30332-0150 United States

This paper presents a foundation for an integrated approach to the design of controls and diagnostics in reliable control systems. In this approach the control module and diagnostic module of the control system are designed together, instead of independently, thereby accounting for the interactions which occur between these two modules in a functioning control system. This approach makes use of a generalization of the familiar two parameter controller known as the four parameter controller. This controller has two vector inputs (rather than one) and two vector outputs;correspondingly, this controller is comprised of four matrix parameters (rather than two). The additional controller output may be viewed as a diagnostic output which is monitored to detect and isolate sensor and actuator faults. The presentation develops a parameterization of all four parameter controllers, delineates the fundamental limitations and inherent tradeoffs governing the design of controls and diagnostics, and gives special attention to the issues of control/diagnostic interaction and uncertainty. Several means for effectively resolving these design tradeoffs are proposed and illustrated by way of an example. © 1991 IEEE

关键词： control systems Fault detection Jacobian matrices Monitoring Actuators Neutron spin echo Research and development Aerospace engineering Laboratories uncertain systems

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An Integrated, Full-Range Surge control/Rotating Stall Avoidance Compressor control System

An Integrated, Full-Range Surge Control/Rotating Stall Avoid...

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American control Conference (ACC)

作者： O. O. Badmus C. N. Nett F. J. Schork School of Chemical Engineering Georgia Institute of Technology Atlanta GA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA

In this paper we present an integrated compressor control scheme capable of achieving simultaneous surge control and rotating stall avoidance over the full range of compressor operation. The approach adopted in this paper is based on a combination of closed-loop feedback control and open-loop feedforward control of throttle valve area. The feedback control is based on a compressor mass fiow measurment. The feedforward control is based on measuremets of inlet and outlet pressure and temperature. Both the feedback and feedforward controller parameters are continuously scheduled as a function of nominal operating conditions. This approach achieves simultaneous surge control and rotating stall avoidance, over the full range of compressor operation, in the face of i) inlet and outlet pressure and temperature disturbances, and ii) variations in the demanded values of both compressor speed and mass flow. Alternative approaches involving plenum pressure feedback, widely reported in literature, are shown to posess inherent performance limitations not possessed by the mass flow feedback scheme presented here.

关键词： control systems Surges Open loop systems Feedback control Pressure control Temperature control Valves Pressure measurement Weight control Temperature distribution

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A General Nonlinear Dynamical Analysis of a Second-Order, One-Dimensional, Theoretical Compression System Model

A General Nonlinear Dynamical Analysis of a Second-Order, On...

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American control Conference (ACC)

作者： S. M. Oliva C. N. Nett School of Mathematics Georgia Institute of Technology Atlanta CA USA Georgia Institute of Technology Laboratory for Identification and Control of Complex Highly Uncertain Systems School of Applied and Engineering Physics Atlanta CA USA

In this paper we present a nonlinear dynamical analysis of a second-order, one-dimensional, theoretical compression system model. As in previous analyses of this type, a nondimensional speed parameter is regarded as a variable system parameter. However, in contrast to previous analyses of this type, here the nondimensional compressor and throttle characteristics embedded within the model are also regarded as variable system parameters. This results in an explicit characterization of the way in which the nonlinear dynamical behavior exhibited by the model depends on these characteristics. In applications this characterization provides guidelines for specifying unmeasurable details of these characteristics in such a way as to ensure that the nonlinear dynamical behavior exhibited by the model corresponds to that observed in the underlying physical compression system.

关键词： Surges Bifurcation Predictive models Stability Guidelines control systems Analytical models Closed-form solution Sufficient conditions Fluid flow

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Worst Case System identification in l1: Optimal Algorithms and Error Bounds

Worst Case System Identification in l1: Optimal Algorithms a...

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American control Conference (ACC)

作者： C. A. Jacobson C. N. Nett Department of Electrical and Computer Engineering North Eastern University Boston MA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems (LICCHUS) School Institute of Technology Georgia Institute of Technology Atlanta GA USA

This paper analyzes worst case identification of linear shift invariant systems with an l 1 error criterion. A characterization of optimal algorithms and intrinsic errors of identification is given. The application of this characterization is made to identification in l 1 . The assumed apriori information on the plant are bounds on the system gain and decay rate of the impulse response of the unknown system and the experimental data is assumed to be a finite set of corrupted impulse or step response samples of the systems. Comparisons are made with the H ∞ system identification problem. Comments on the l 1 identification of small signal models of smooth nonlinear discrete time systems are made.

关键词： System identification Robust control Convolution Jacobian matrices Algorithm design and analysis Signal processing Discrete time systems control system synthesis Nonlinear control systems Design methodology

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A System-Theoretic Appropriate Realization of the Empty Matrix Concept

A System-Theoretic Appropriate Realization of the Empty Matr...

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American control Conference (ACC)

作者： C. N. Nett W. M. Haddad Laboratory for Identification and Control of Complex Highly Uncertain Systems (LIC-CHUS) Georgia Institute of Technology School of Applied and Engineering Physics Atlanta GA USA Department of Mechanical and Aerospace Engineering Florida Institute of Technology Melbourne FL USA

In this paper we propose an algebraic realization of the empty matrix concept which is appropriate for system-theoretic applications. This realization differs considerably from the realization currently implemented by The Mathworks, Inc. within their MATLAB program. We demonstrate by repeated example the utility of our realization of the empty matrix concept, and through these same examples indicate the deficiencies of the current MATLAB realization of this concept. These examples fully delineate how the empty matrix concept can be utilized to transparently handle static and/or single vector input, single vector output systems within the more general context of dynamic, two vector input, two vector output systems.

关键词： Matrices MATLAB Aerospace engineering Large-scale systems Programming Aerodynamics Automatic control control systems uncertain systems Aerospace control

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