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Reference Tracking (reference + tracking)

Distribution by Scientific Domains

Engineering	60%

Selected Abstracts

Model reference adaptive control using a low-order controller

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 3 2001
Daniel E. Miller
Abstract In the model reference adaptive control problem, the goal is to force the error between the plant output and the reference model output asymptotically to zero. The classical assumptions on a single-input,single-output (SISO) plant is that it is minimum phase, and that the plant relative degree, the sign of the high-frequency gain, and an upper bound on the plant order are known. Here we consider a modified problem in which the objective is weakened slightly to that of requiring that the asymptotic value of the error be less than a (arbitrarily small) pre-specified constant. Using recent results on the design of generalized holds for model reference tracking, here we present a new switching adaptive controller of dimension two which achieves this new objective for every minimum phase SISO system; no structural information is required. Copyright © 2001 John Wiley & Sons, Ltd. [source]

A levenberg,marquardt learning applied for recurrent neural identification and control of a wastewater treatment bioprocess

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 11 2009
Ieroham S. Baruch
The paper proposed a new recurrent neural network (RNN) model for systems identification and states estimation of nonlinear plants. The proposed RNN identifier is implemented in direct and indirect adaptive control schemes, incorporating a noise rejecting plant output filter and recurrent neural or linear-sliding mode controllers. For sake of comparison, the RNN model is learned both by the backpropagation and by the recursive Levenberg,Marquardt (L,M) learning algorithm. The estimated states and parameters of the RNN model are used for direct and indirect adaptive trajectory tracking control. The proposed direct and indirect schemes are applied for real-time control of wastewater treatment bioprocess, where a good, convergence, noise filtering, and low mean squared error of reference tracking is achieved for both learning algorithms, with priority of the L,M one. © 2009 Wiley Periodicals, Inc. [source]

Non-diagonal MIMO QFT controller design reformulation

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 9 2009
Mario Garcia-Sanz
Abstract This paper presents a reformulation of the full-matrix quantitative feedback theory (QFT) robust control methodology for multiple-input,multiple-output (MIMO) plants with uncertainty. The new methodology includes a generalization of previous non-diagonal MIMO QFT techniques; avoiding former hypotheses of diagonal dominance; simplifying the calculations for the off-diagonal elements, and then the method itself; reformulating the classical matrix definition of MIMO specifications by designing a new set of loop-by-loop QFT bounds on the Nichols Chart, which establish necessary and sufficient conditions; giving explicit expressions to share the load among the loops of the MIMO system to achieve the matrix specifications; and all for stability, reference tracking, disturbance rejection at plant input and output, and noise attenuation problems. The new methodology is applied to the design of a MIMO controller for a spacecraft flying in formation in a low Earth orbit. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Polynomial control: past, present, and future

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 8 2007
Vladimír Ku
Abstract Polynomial techniques have made important contributions to systems and control theory. Engineers in industry often find polynomial and frequency domain methods easier to use than state equation-based techniques. Control theorists show that results obtained in isolation using either approach are in fact closely related. Polynomial system description provides input,output models for linear systems with rational transfer functions. These models display two important system properties, namely poles and zeros, in a transparent manner. A performance specification in terms of polynomials is natural in many situations; see pole allocation techniques. A specific control system design technique, called polynomial equation approach, was developed in the 1960s and 1970s. The distinguishing feature of this technique is a reduction of controller synthesis to a solution of linear polynomial equations of a specific (Diophantine or Bézout) type. In most cases, control systems are designed to be stable and meet additional specifications, such as optimality and robustness. It is therefore natural to design the systems step by step: stabilization first, then the additional specifications each at a time. For this it is obviously necessary to have any and all solutions of the current step available before proceeding any further. This motivates the need for a parametrization of all controllers that stabilize a given plant. In fact this result has become a key tool for the sequential design paradigm. The additional specifications are met by selecting an appropriate parameter. This is simple, systematic, and transparent. However, the strategy suffers from an excessive grow of the controller order. This article is a guided tour through the polynomial control system design. The origins of the parametrization of stabilizing controllers, called Youla,Ku,era parametrization, are explained. Standard results on reference tracking, disturbance elimination, pole placement, deadbeat control, H2 control, l1 control and robust stabilization are summarized. New and exciting applications of the Youla,Ku,era parametrization are then discussed: stabilization subject to input constraints, output overshoot reduction, and fixed-order stabilizing controller design. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Simultaneous Automatic Control of Oxygen and Carbon Dioxide Blood Gases During Cardiopulmonary Bypass

ARTIFICIAL ORGANS, Issue 6 2010
Berno J.E. Misgeld
Abstract In this work an automatic control strategy is presented for the simultaneous control of oxygen and carbon dioxide blood gas partial pressures to be used during cardiopulmonary bypass surgery with heart,lung machine support. As the exchange of blood gases in the artificial extracorporeal lung is a highly nonlinear process comprising varying time delays, uncertainties, and time-varying parameters, it is currently being controlled manually by specially trained perfusionist staff. The new control strategy includes a feedback linearization routine with augmented time-delay compensation and two external linear gain-scheduled controllers, for partial oxygen and carbon dioxide pressures. The controllers were robustly tuned and tested in simulations with a detailed artificial lung (oxygenator) model in cardiopulmonary bypass conditions. Furthermore, the controllers were implemented in an ex vivo experiment using fresh porcine blood as a substitute fluid and a special deoxygenation technique to simulate a patient undergoing cardiopulmonary bypass. Both controllers showed robust stability during the experiments and a good disturbance rejection to extracorporeal blood flow changes. This automatic control strategy is proposed to improve patient's safety by fast control reference tracking and good disturbance rejection under varying conditions. [source]