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American Control Conference (ACC)

作者： R.L. Kosut B.D.O. Anderson Integrated Systems Inc. Santa Clara CA USA Department of Systems Engineering & Cooperative Research Center for Robust and Adaptive Systems Australian National University Canberra ACT Australia

Two least-squares based methods are presented for obtaining ARX model sets. The first is obtained using properties of high-order ARX models and the second uses a stochastic embedding scheme on the residuals from an ARX model of any order. Either of the ARX model sets is useful for robust control of systems with uncertain parameters. Using the high order ARX model approach, the parameter uncertainty lies in a confidence ellipsoid. Using the stochastic embedding approach, the parameter uncertainty is in a confidence box. For scalar plants, both cases can be handled using convex programming to obtain the exact stability robustness margin for a particular controller. However, because the uncertainty description is probabilistic, the robustness property has to be associated with a confidence level, i.e., a probability of stability.

关键词： Parameter estimation robust control Australia Stochastic processes Uncertain systems robust stability systems engineering and theory robustness adaptive systems Uncertainty

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Solution Set Properties for Errors-in-Variables Problems

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IFAC Proceedings Volumes 1994年第8期27卷 1127-1132页

作者： A.D.O. Anderson M. Deistler Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Australian National University Canberra ACT 0200 AUSTRALIA University of Technology Vienna Institute of Econometrics Operations Research and Systems Theory Argentimerstraβe 8 A-1040 Vienna AUSTRIA

This paper examines and refutes a conjecture, to the effect that the solution set for a general (real) static errors-in-variables problem is a union of convex polytopes. The conjecture is disproved, through detailed examination of particular errors-in-variables problems with four variables. The solution set is contained in a union of a finite set of surfaces, all intersecting in straight lines, but in general, one of the surfaces is not flat.

关键词： Identification linear systems parameter estimation system identification

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Locally C/sup 1/ interpolation of functions on an arbitrary simplex mesh using a simple feed-forward perceptron

Locally C/sup 1/ interpolation of functions on an arbitrary ...

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International Conference on Neural Networks

作者： R. Mahony J. Moore L. Dailey Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Australian National University Canberra ACT Australia Boeing Aircraft Corporation Seattle USA

In this paper we present a solution to a C/sup 1/ interpolation problem for lower dimensional data in Euclidean space. The solution presented falls into two parts, the first being the formulation of an abstract simplex mesh that parametrizes the data while the second part presents an interpolation algorithm based on the structure of a simple feed-forward perceptron. To emphasise the connection between our approach and classical spline interpolation we choose cubic polynomial activation functions in the neural units of the perceptron.

关键词： Interpolation Feedforward systems Aircraft Spline Force control robustness adaptive systems Piecewise linear approximation Mesh generation Aerospace engineering

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On robust performance improvement through the windsurfer approach to adaptive robust control

On robust performance improvement through the windsurfer app...

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IEEE Conference on Decision and Control

作者： W.S. Lee B.D.O. Anderson R.L. Kosut I.M.Y. Mareels Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Australian National University Canberra ACT Australia Integrated Systems Inc. Santa Clara CA USA

In this paper it is shown that, given a stable strictly proper model of a stable strictly proper plant, we can improve the performance robustness of the closed-loop system through the windsurfer approach to adaptive robust control if the deterioration in performance robustness caused by increasing the closed-loop bandwidth resulted in a sufficiently high signal-to-noise ratio for a certain closed-loop output error. This is the key conclusion arising from an examination of a series of questions about the procedure that focus on what one would like to do, and what one can do. Situations that may cause the iterative identification and control design process in the windsurfer approach to terminate prematurely are also indicated.< >

关键词： robust control Programmable control adaptive control Bandwidth Transfer functions robust stability Filters robustness Control design Frequency

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Relating H/sub 2/ and H/sub /spl infin//-norm bounds for sampled-data systems

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IEEE Transactions on Automatic Control 1997年第6期42卷 858-863页

作者： S. Hara B.D.O. Anderson H. Fujioka Department of Systems Engineering and Cooperative Research Center for Robust and Adaptive Systems School of Information Sciences & Engineering Australian National University Canberra Australia Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Yokohama Japan Department of Mechanical Engineering for Computer Controlled Machinery Faculty of Engineering Osaka University Suita Osaka Japan

We relate the H/sub /spl infin// and H/sub 2/ norms for multi-input/multi-output sampled-data feedback control systems, where a continuous-time plant is controlled by a digital compensator with hold and sampler. Upper bounds on both H/sub 2/ and H/sub /spl infin// norms are obtained based on fundamental relations derived by two different approaches, namely the hybrid state-space approach and the fast sampling and lifting approach.

关键词： H infinity control Riccati equations Automatic control robustness Output feedback Control system synthesis Optimal control Entropy Attenuation Control systems

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Relating H/sub 2/ and H/sub /spl infin// norm bounds for hybrid systems

Relating H/sub 2/ and H/sub /spl infin// norm bounds for hyb...

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IEEE Conference on Decision and Control

作者： S. Hara B.D.O. Anderson H. Fujioka Department of Systems Science Tokyo Institute of Technology Yokohama Japan Department of Systems Engineering and Cooperative Research Center for Robust and Adaptive Systems Research School of Engineering Information Sciences & Engineering Australian National University Canberra ACT Australia

The authors relate the H/sub /spl infin// and H/sub 2/ norms for a type of MIMO hybrid system, which includes sampled-data feedback control systems, where a continuous-time plant is controlled by a digital compensator with hold and sampler. First, the authors derive the H/sub /spl infin// norm bounds for MIMO purely continuous and discrete-time systems given information concerning the location of the poles. The results are the same as those for the SISO case. Second, the authors describe upper bounds on both H/sub 2/ and H/sub /spl infin// norms for hybrid systems, based on fundamental relations derived by two different approaches, namely the hybrid state space approach and the fast sampling and lifting approach. The authors also show the properties and interpretation of a residual appearing in the bounds and investigate the upper bound of the H/sub 2/ norm for a purely continuous-time system based on the result for the general hybrid case.< >

关键词： MIMO Control systems Upper bound Optimal control Control system synthesis Hydrogen robust control Feedback control Digital control Joining processes

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Excitation Versus Control Issues in Closed Loop Identification of Plant Models for a Sugar Cane Crushing Mill 1

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IFAC Proceedings Volumes 1993年第2期26卷 121-124页

作者： A.G. Partanen R.R. Bitmead formerly with Computer Services Department CSR Limited Victoria Mill Ingham Queensland 4850 Australia Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Australian National University Canberra ACT 0200 Australia

This paper addresses the selection of excitation signals to enhance the identification of a linear model of a plant system from data collected whilst the plant is operating under closed loop control. Theoretical results are developed which characterize the effective frequency weighting induced by the closed loop to the modelling criterion. These results then are used to establish the cause of ‘identification of the controller’ and to study mechanisms for influencing the model fit to focus on the plant system through the selection of exogenous excitation signals introduced to the loop. Experimental results of closed loop identification with and without excitation on the plant inputs are presented. The plant models identified here were used to develop MISO LQG controllers for a Crushing Plant in a Sugar Mill.

关键词： Experiment Design Closed Loop Identification Excitation

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Output feedback risk-sensitive control and differential games for continuous-time nonlinear systems

Output feedback risk-sensitive control and differential game...

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IEEE Conference on Decision and Control

作者： M.R. James J.S. Baras R.J. Elliott Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Australian National University Canberra ACT Australia Department of Statistics and Applied Probability University of Alberta Edmonton AB Canada

In this paper we carry out a formal analysis of an output feedback risk-sensitive stochastic control problem. Using large deviation limits, this problem is related to a deterministic output feedback differential game. Both problems are solved using appropriate information states. The use of an information state for the game problem is new, and is the principal contribution of our work. Our results have important implications for the nonlinear robust stabilization problem.< >

关键词： Output feedback Nonlinear control systems Control systems Nonlinear systems Stochastic systems robust control robustness adaptive systems systems engineering and theory Risk analysis

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Linearly Constrained LQ and LQG Optimal Control

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IFAC Proceedings Volumes 1996年第1期29卷 1110-1115页

作者： A.E.B. Lim J.B. Moore L. Faybusovich Department of Systems Engineering and Cooperative Research Centre for Robust and Adaptive Systems Research School of Information Sciences and Engineering Australian National University Canberra ACT 0200 Australia. Department of Mathematics University of Notre Dame Mail Distribution Center Notre Dame IN 46556.

It has recently been shown that the logarithmic barrier method for solving finite-dimensional, linearly constrained quadratic optimization problems can be extended to an infinite-dimensional setting with complexity estimates similar to the finite dimensional case. As a consequence, an efficient computational method for solving the linearly constrained LQ control problem is now available. In this paper, we solve the linearly constrained LQG control problem by generalizing the Separation Theorem. We show how the logarithmic barrier method can be used to determine the optimal control for the constrained LQG problem.

关键词： Optimal control linear constraints interior-point methods logarithmic barrier method LQG control Separation Theorem

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Direct Controller Design from Plant Data

Direct Controller Design from Plant Data

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American Control Conference (ACC)

作者： Vincent Wertz Robert Bitmead Robert L. Kosut Chercheur Qualifié CNRS Belgium Cooperative Research Centre for Robust and Adaptive Systems Department of Systems Engineering RSPhysSE National University Canberra ACT Australia Integrated Systems Inc. Santa Clara CA USA

Methods are investigated in which controllers (simple memoryless nonlinear functions of the output of the plant) are directly estimated from input-output data without a model of the plant. A procedure is proposed which first selects good data sequences according to some control objective and then estimates the controller parameters directly from the selected sequences. Connections are drawn with other methods of direct controller design, e.g. fuzzy logic control or artificial neural networks control and general issues regarding these methods, such as a priori knowledge and experiment design, are considered.

关键词： Data mining robust control Programmable control adaptive control Gold Parameter estimation Fuzzy logic Artificial neural networks Intelligent control Output feedback

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