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Control Theory and Applications, IEE Proceedings -

Issue 2 • Date 23 March 2004

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Displaying Results 1 - 15 of 15
  • Robust high speed and high precision linear motor direct-drive XY-table motion system

    Page(s): 166 - 173
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1405 KB)  

    Linear motor direct-drive XY-table mechanisms commonly suffer from significant mechanical resonances at high acceleration rates. These problems can be solved by using a quantitative-feedback-theory-based tracking control scheme. This scheme has an inner-loop robust velocity controller, an outer-loop position controller and an auto-tuning feedforward compensator. A high order velocity controller is especially designed to reduce the resonance uncertainty as well as attenuating the external disturbances and sensor noises. The resulting control system is fully implemented and validated on a direct-drive XY-table with a maximum 6.8g (1g = 9.81 m/s2) high acceleration profile motion on tens of mass-production machines. View full abstract»

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  • Tracking control of the boost converter

    Page(s): 218 - 224
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1352 KB)  

    The tracking control problem of amplifying converters encompasses an important practical concern and a challenging theoretical problem. These converters are nonlinear, nonminimum phase systems with saturated control and a highly variable parameter (the load). Such characteristics make amplifying converters devices difficult to control, even for the regulation case. Several aspects of the tracking control problem of the boost converter are addressed. A characterisation of the signal the converter is able to follow is given. The relationship between the parameter values and the tracking error is established, and it is shown that adequate parameters for the DC-to-DC converter are not always suitable for DC-to-AC conversion. View full abstract»

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  • Imposing steady-state performance on identified nonlinear polynomial models by means of constrained parameter estimation

    Page(s): 174 - 179
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1343 KB)  

    The authors present a procedure that permits the use of steady-state information to constrain the identification of nonlinear polynomial models. Such a procedure has three main steps. First, a general framework is provided that relates the static function of nonlinear global polynomial models to their terms and parameters. Second, using standard nonlinear programming techniques, a rational function is fitted to the system static function, which is assumed to be known and is used as auxiliary information. Finally, the information gathered in the first two steps is used to write a set of equality constraints that are exactly satisfied by a standard constrained least-squares algorithm used to estimate the parameters of the identified model. It is shown that the resulting model will always have the specified static nonlinearity and will use additional degrees of freedom to fit the dynamics underlying the observed data. View full abstract»

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  • Diagonal dominance using LMIs

    Page(s): 225 - 233
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1428 KB)  

    A new method for determining a constant precompensator for reducing the effects of interactions in multivariable systems is presented. It is shown that linear matrix inequalities (LMIs) can be used in the design of precompensators to achieve diagonal dominance. The algorithm presented alleviates the necessity of choosing a suitable frequency in designing such a precompensator, as required by previous methods. The method is then modified to reduce the conservatism by the introduction of scaling as an LMI variable and a path-shaping matrix. The path-shaping matrix enables a designer to find an optimal precompensator to achieve a specific forward path structure. The algorithm is applied to a Rolls Royce Spey jet engine, and the results obtained are comparable with previously obtained results. However, it gives a more systematic methodology for designing such precompensators. View full abstract»

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  • Predictive control of general nonlinear systems using approximation

    Page(s): 137 - 144
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1355 KB)  

    The paper addresses a tracking problem for general nonlinear systems using model predictive control (MPC). After approximation of the tracking error in the receding horizon by its Taylor-series expansion to any specified order, an analytic solution to the MPC is developed and a closed-form nonlinear predictive controller is presented. Unlike other nonlinear-model predictive control (NMPC), there is a built-in integral action in the developed scheme and the implementation issues are discussed. It is pointed out that the proposed NMPC derived using approximation can stabilise the original nonlinear systems if certain conditions, which can be met by properly choosing predictive times and the order for Taylor expansion, are satisfied. Simulation demonstrates the effectiveness of the proposed NMPC. View full abstract»

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  • Robust MIMO control-system design using eigenstructure assignment and QFT

    Page(s): 198 - 209
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1427 KB)  

    An approach to robust control design for a multi-input/multi-output (MIMO) plant using eigenstructure assignment (EA) and quantitative feedback theory (QFT) is presented and applied to the design of a lateral flight control system. EA techniques are introduced to give an initial feedback control design for the nominal plant model, providing decoupling between the multiple control channels. The QFT method for single-input/single-output (SISO) plants is used to obtain robust stability under the given plant-parameter uncertainties. Detailed designs are conducted with both the proposed EA/QFT approach and the direct MIMO QFT approach. The design results demonstrate the good performance and features of the proposed EA/QFT approach that may be achieved. View full abstract»

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  • Batch-to-batch optimal control of nonlinear batch processes based on incrementally updated models

    Page(s): 158 - 165
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1376 KB)  

    An iterative learning control (ILC) strategy for the tracking control of product quality in agile batch manufacturing processes is proposed. The ILC strategy is based on a linearised model of the controlled process that is initially identified from a minimum amount of historical process operation data and is updated after each batch run. The amount of historical process operation data in agile responsive batch manufacturing processes is usually limited and might not be sufficient for model identification if the model contains a large number of model parameters. To address this issue, the number of control intervals in a batch is set to be increased from run to run. Initially, the number of control intervals in a batch is set to a small value so that the linearised model contains a small number of model parameters, which can be estimated using historical process operation data. Control actions for a new batch run are calculated using ILC. Then the model is updated by using the augmented data set incorporating data from the latest batch run while the number of control intervals in a batch is increased by one until reaching its maximum value. The procedure is repeated from batch to batch. The proposed methodology is illustrated on a simulated batch reactor. The simulation results demonstrate that the proposed technique requires minimum historical process operation data and can improve control performance from batch to batch. View full abstract»

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  • Multiple models for adaptive control to improve the performance of minimum variance regulators

    Page(s): 210 - 217
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1365 KB)  

    The design of a minimum variance regulator for systems operating in dynamical uncertain environments is considered. For minimum variance self-tuning control of an unknown linear time-invariant system, a stable control strategy is developed that improves the transient response by using multiple models to describe the different environments and switching between the relative controllers. The controller is determined at every time instant by the model which best approximates the plant. The performance of the controller is evaluated by a set of simulation tests. View full abstract»

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  • Sparse controller realisation with small roundoff noise

    Page(s): 246 - 251
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1340 KB)  

    The effect of roundoff noise in a digital controller is analysed for a digital feedback control system. An analytical expression for the roundoff noise gain, defined as the ratio between the variances of the output error and the rounding error, is obtained. The problem of identifying the minimum roundoff noise realisations can be solved using an existing procedure. Noting that the optimal realisations are fully parametrised, based on a polynomial operator approach a new sparse controller realisation is derived. This realisation is a generalisation of the direct forms in the classical shift operator and the prevailing delta-operator. It provides more degrees of freedom with which to reduce the roundoff noise. The problem of finding optimal polynomial operators can be solved by an exhaustive search, and a design example is given. It is shown that with the proposed sparse realisation the optimal polynomial operators can outperform the shift- and delta-operators. View full abstract»

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  • Instability of an oscillator amplitude control system

    Page(s): 194 - 197
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1313 KB)  

    A closed-loop amplitude control system must be included in the design of an electronic oscillator when a sinusoidal output of very low distortion is required. The instability of such a control system is considered and an experimental oscillator is used to check the theoretical predictions. View full abstract»

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  • Design method for an adaptive robust controller with L2-gain disturbance attenuation for nonlinear systems with uncertainty

    Page(s): 152 - 157
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1345 KB)  

    A nonlinear feedback control design for the adaptive robust H control problem for nonlinear systems with gain bounded uncertainty is presented. An existing control scheme developed for nonlinear systems with relative degree of one is extended to the case where nonlinear systems have general relative degree. A Lyapunov function is constructed that ensures not only the stability of the closed-loop system but also satisfies the dissipation inequality ensuring L2-gain performance. Then the controller can be obtained by the recursive use of the existing control scheme. A closed-form solution for the nonlinear H control problem is provided without using a Hamilton-Jacobi inequality in the general relative degree case. Sufficient conditions which nonlinear systems should satisfy for solvability of the problem are provided. View full abstract»

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  • Adaptation, modelling of dynamic drives and controller design in servomechanism pneumatic systems

    Page(s): 234 - 245
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1810 KB)  

    Problems associated with the application of modern control approaches to industrial servomechanism systems, developed using pneumatic techniques, are presented and discussed. Two major tasks for servosystems are investigated: point-to-point and trajectory-tracking control. Presentations of the drive system, based on fundamental phenomenology equations and statistically identified models, are introduced and discussed. This knowledge combined with identified roles for drives leads to approaches that can be useful in the design of appropriate controller algorithms for 'high-tech' servosystems. Their variety, including state-space control, fast adaptation control, predictive control and multipurpose (movement and force) control is presented. Application of these techniques in industrial conditions involves different technical problems, e.g. measurability of signals, time limit on control values or sensitivity to variations of load, working regime and supply conditions. Proposals on how to cope with these problems are described. Extended testing under industrial conditions is described briefly. View full abstract»

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  • Markov-chain Monte-Carlo approach for association probability evaluation

    Page(s): 185 - 193
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1420 KB)  

    Data association is one of the essential parts of a multiple-target-tracking system. The paper introduces a report-track association-evaluation technique based on the well known Markov-chain Monte-Carlo (MCMC) method, which estimates the statistics of a random variable by way of efficiently sampling the data space. An important feature of this new association-evaluation algorithm is that it can approximate the marginal association probability with scalable accuracy as a function of computational resource available. The algorithm is tested within the framework of a joint probabilistic data association (JPDA). The result is compared with JPDA tracking with Fitzgerald's simple JPDA data-association algorithm. As expected, the performance of the new MCMC-based algorithm is superior to that of the old algorithm. In general, the new approach can also be applied to other tracking algorithms as well as other fields where association of evidence is involved. View full abstract»

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  • Properties of zeros of discretised system using multirate input and hold

    Page(s): 180 - 184
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1316 KB)  

    The paper investigates the proprieties of limiting zeros of a discrete-time system discretised by the use of multirate input and hold. The stability conditions of the limiting zeros for sufficiently small sampling periods are derived in the case that the relative degree of a continuous-time system is equal to two or three. It is also shown that the intersample behaviour arising from the multirate input can be localised by appropriately selecting the design parameters based on the stability condition of the zeros. View full abstract»

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  • Design of multilevel perturbation signals with harmonic properties suitable for nonlinear system identification

    Page(s): 145 - 151
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1319 KB)  

    A method is described for determining the levels of multilevel pseudorandom perturbation signals generated from maximum-length sequences in Galois fields that give the signals the desirable characteristics that their even harmonics are suppressed and their odd harmonics are uniform. The method uses the fact that a short sequence comprised of the signal levels converted from the nonzero field elements taken in a particular order must have corresponding characteristics. Analytical expressions are obtained for the signal level conversions that are necessary for the signal to possess these characteristics. The results are tabulated in symbolic form for 3-level, 5-level and 7-level signals generated in the fields GF(3), GF(5), GF(7), GF(9), GF(11) and GF(13). The method is then extended to signals in which harmonic multiples of 2 and 3 are suppressed and nonzero harmonics are uniform, and similar results are tabulated for GF(7) and GF(13). An example is used to illustrate the application of the results. View full abstract»

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