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Control Theory and Applications, IEE Proceedings D

Issue 5 • Date September 1982

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Displaying Results 1 - 14 of 14
  • Two-dimensional curve fitting and prediction using spectral analysis

    Page(s): 145 - 150
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (728 KB)  

    A curve-fitting or prediction problem for two-dimensional or cyclic processes is defined and solved using spectral techniques. The assumed statistical model is structurally similar to the Karhunen-Lo¿¿ve expansion, and the technique can be implemented using the singular-value decomposition. Two examples using published data illustrate the feasibility of the method and the peculiarities associated with the problem. View full abstract»

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  • Macroeconomic policy formulation: A contribution from control theory

    Page(s): 151 - 162
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1686 KB)  

    The paper describes applications of control theory methods to macroeconomic policy formulation. The use of modelling concepts and techniques arising from control theory are discussed. Applications of control methods to macroeconomic models are described both for linear and for large nonlinear models. In the case of linear models, a minimal state-space representation is obtaine, a quadratic performance index adopted, and, assuming a Gaussian distribution of disturbances, the policy design problem is formulated in terms of a classical optimal control (LQG) framework. For large nonlinear models, and earlier approach involving the control of such systems using small linearised models is discussed initially. Subsequently, a direct approach, using a nonlinear optimisation algorithm, for computing optimal policies is discussd. The derivation of parametrised feedback laws and robust controls in such an optimisation setting is also described. View full abstract»

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  • Three-level hierarchical approach to the joint problem of system identification and optimisation

    Page(s): 163 - 166
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (382 KB)  

    The paper presents a three-level hierarchical approach for solving the joint problem of system identification and optimisation. It is then applied to a batch penicillin fermentation process using a microprocessor. Detailed information about the microprocessor system utilised is given. View full abstract»

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  • Structure of large stochastic optimal and suboptimal systems

    Page(s): 167 - 176
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1059 KB)  

    The optimal stochastic regulator is derived for systems which can be decomposed into subsystems with measurable state varibles and subsystems in which only noisy output measurements are available. The solution involves direct state feedback from the former subsystems and feedback via a set of Kalman filters for the latter subsystems. The total order of the Kalman filters equals that of the unmeasurable subsystems. The use of direct state feedback rather than state-estimate feedback is very desirable: the system becomes more robust, nonlinearities have less effect and, since Kalman filter are not needed for these subsystems, modelling errors are reduced. Having decomposed a large system, it is natural to ask whether subsystems can be started and controlled independently before the complete feedback control is applied. Conditions are determined where a sequential start-up procedure for the optimal system is possible. Simplifications to the structure of the controllers for servomechanisms are also considered. View full abstract»

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  • Improvement of system performance by the use of time-delay elements

    Page(s): 177 - 181
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (498 KB)  

    The paper explores the possibility of performance improvement by the use of added delay elements. The counterintuitive phenomenon of `improvement by mismatch¿¿ has been noted by several authors in the context of predictor control. This phenomenon is illustrated using a second-order example, and, in the light of this, it is demonstrated how it also may be improved by the use of delay elements. A third-order example of delay-free system improvement is described. A technique for producing good first-order estimates of design parameters is presented View full abstract»

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  • Electrical vibration damper

    Page(s): 182 - 188
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (685 KB)  

    A method of reducing stationary vibrations in revolving systems by using a vibration-damper system with a two-phase servomotor is proposed. The additional vibration source adopted here eliminates the vibration within one sampling period by using a sampled-data control system which makes use of the finite-settling-time method. The system is demonstrated by applying the additional vibration source to eliminate the second-harmonic vibration produced by the two-phase servomotor of a speed-control system. Tests on the system indicate that the vibration on the shaft can be reduced to zero. View full abstract»

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  • Relative stability test for continuous and sampled-data control systems using the generalised sign matrix

    Page(s): 189 - 192
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (299 KB)  

    An algorithm is developed to perform a relative stability test for time-invariant systems using the generalised sign matrix. The method is then extended to sampled-data control systems through bilinear transformation. The algorithm is efficient and can be easily programmed. View full abstract»

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  • Low-sensitivity observer-compensator design for two-dimensional digital systems

    Page(s): 193 - 200
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (616 KB)  

    The problem considered in the paper refers to the general area of developing design and computational algorithms for analysing low-sensitivity time-invariant multivariable two-dimensional systems using output feedback. It is seen that the matrix-minimum principle can be used to study two-dimensional digital systems with incomplete state information for the implementation of a low-sensitivity feedback law. The results show that an observer can be used in addition to the output vector to estimate the state of the system, which in turn is used for implementing the feedback law. View full abstract»

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  • Matrix fraction description approach to decentralised control

    Page(s): 201 - 205
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (543 KB)  

    A two-channel linear system ¿¿ is given, defined by its transfer matrix G(s), for which a (right) matrix fraction description in the form G(s) = R(s) P¿¿1 (S) is also provided. Local output feedbacks of the form ui = ¿¿ Kiyi are considered, and their effect on the system ¿¿ is studied via the so-called D-controllability problem. This problem is solved using the above definition of ¿¿, and a simple criterion for its solvability is presented involving suitable submatrices of R(S) and P(S). Finally, some results concerning the decentralised stabilisability problem, and the connection to decentralised fixed modes, are also given. View full abstract»

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  • D-controllability of linear systems defined by their transfer matrices

    Page(s): 206 - 210
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (520 KB)  

    A two-channel system defined by its transfer function G(S) is considered, and its controllability with the one of its input channels is examined after the introduction of a local output feedback with respect to the other channel (termed D-controllability). A criterion is given for D-controllability in terms of a (right) matrix fraction description G(S) = R(S)P¿¿1 (S) of its transfer matrix G(S). View full abstract»

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  • Dynamical Hierarchical Control

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    Freely Available from IEEE
  • Linear Control System Analysis and Design

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    Freely Available from IEEE
  • Practical Troubleshooting Techniques for Microprocessor Systems

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    Freely Available from IEEE
  • Stochastic and Deterministic Averaging Processors

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    Freely Available from IEEE