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Volume 151
Issue 4
IEE Proceedings - Control Theory and Applications
Volume 151, Issue 4, July 2004
Volumes & issues:
Volume 151, Issue 4
July 2004
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- Author(s): T.H.S. Abdelaziz and M. Valášek
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 377 –385
- DOI: 10.1049/ip-cta:20040660
- Type: Article
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p.
377
–385
(9)
A procedure for solving the pole-placement problem for a linear single-input/single-output (SISO) systems by state-derivative feedback is described. This pole-placement problem is always solvable for controllable systems if all eigenvalues of the original system are nonzero. Then any arbitrary closed-loop poles can be placed to achieve the desired system performance. The solution procedure results in a formula similar to the Ackermann one. Its derivation is based on the transformation of a linear SISO system into Frobenius canonical form by co-ordinate transformation, then solving the pole-placement problem by state-derivative feedback and transforming the solution into the original co-ordinates. The solution is also extended to time-varying systems. - Author(s): G. Hearns ; P. Reeve ; P. Smith ; T. Bilkhu
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 386 –394
- DOI: 10.1049/ip-cta:20040642
- Type: Article
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p.
386
–394
(9)
Hot strip mills are processes with a very high throughput of products. They are highly developed capital intensive and competitive businesses where control systems are essential to maintain product quality and production efficiency. Even small improvements in the accuracy of the product and mill availability yield significant savings for the steel producer. To this end the development and trial implementation of a multivariable controller to control the gauge and mass flow for one stand and interstand in a tandem hot strip mill is described. A feature of the design is that no new or additional equipment to that installed for the conventional control system is required for the multivariable design. Gauge control is essential to product quality while regulating mass flow is important for stable operation of the complete mill. Gauge and mass flow are tightly coupled. The control design, which uses state feedback and estimation, is described along with the issues necessary for a practical implementation. Inherent in the multivariable design is the explicit ability to trade-off gauge and mass flow performance against each other. The performance of the controller from a trial implementation on a seven-stand hot strip mill is analysed and compared with the existing mill controllers. - Author(s): F.-J. Lin ; C.-H. Lin ; P.-H. Shen
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 395 –406
- DOI: 10.1049/ip-cta:20040489
- Type: Article
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p.
395
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(12)
A variable-structure controller, using a recurrent fuzzy neural network (RFNN) to control the mover position of a permanent-magnet linear synchronous motor (PMLSM) servo drive is developed. A variable-structure adaptive (VSA) controller is first adopted to control the mover position of the PMLSM, where a simple adaptive algorithm is utilised to estimate the uncertainty bounds. Then, to further improve the rate of convergence of the estimation, a variable-structure controller using an RFNN is investigated, in which the RFNN is utilised to estimate the real-time lumped uncertainty. Simulated and experimental results show that the proposed variable-structure controller using an RFNN provides high-performance dynamic characteristics and is robust with regard to plant-parameter variations and external disturbance. Furthermore, comparing with the VSA controller, a smaller control effort is required and the chattering phenomenon is reduced by the proposed variable-structure controller using an RFNN. - Author(s): F.-J. Lin ; C.-H. Lin ; P.-K. Huang
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 407 –416
- DOI: 10.1049/ip-cta:20040652
- Type: Article
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p.
407
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(10)
A sliding-mode recurrent fuzzy neural network control (SMRFNNC) is proposed to control the mover of a permanent-magnet linear synchronous motor (PMLSM) servo drive so as to track a periodic sinusoidal reference trajectory. First, the PMLSM drive system is identified by a recurrent fuzzy neural network identifier (RFNNI) to provide sensitivity information of the drive system to a recurrent fuzzy neural network controller (RFNNC). Next, a sliding-mode adjuster (SMA) is determined according to the sliding mode condition. Then, the SMA is backpropagated through the RFNNI to train the parameters of the RFNNC online. Simulated and experimental results show that the control effort and chattering of the SMRFNNC are smaller than those of sliding-mode control. Moreover, a robust control performance is achieved when uncertainties occur including a nonlinear friction force. - Author(s): Chunguang Li ; Houjun Wang ; Xiaofeng Liao
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 417 –421
- DOI: 10.1049/ip-cta:20040641
- Type: Article
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p.
417
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(5)
The stability problem of Takagi-Sugeno fuzzy systems with time-varying delays and parameter uncertainties is considered. A delay-dependent robust stability criterion is given in terms of linear matrix inequalities by using the Lyapunov-Krasovskii functional method and by applying a generalised Park's inequality for bounding the cross-terms. Examples are given to illustrate the effectiveness of the result. - Author(s): A. Wang and H. Wang
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 422 –428
- DOI: 10.1049/ip-cta:20040488
- Type: Article
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p.
422
–428
(7)
The entropy concept in stochastic systems is used to formulate a control algorithm which minimises the closed-loop randomness for a class of nonlinear dynamic stochastic systems and places the output mean value as close as possible to a given value. Since the entropy measures the randomness of stochastic systems in a more general sense than that of the variance measure for Gaussian random variables, the use of entropy here can produce control algorithms which minimise uncertainties for the closed-loop stochastic systems subjected to any bounded random inputs (generally non-Gaussian). The output probability density function of the system is approximated by the recently developed linear B-spline decoupling model, and the dynamic part of the system links the coefficients of the B-spline expansion with a deterministic control input by a nonlinear affine model. To minimise the randomness of the closed-loop system, the entropy of the output probability density function is included in the proposed performance function. By minimising this performance function, a controller is obtained through a first-order approximation of the ‘logarithm’ function involved in the output entropy calculations. An illustrative example is used to show the use of the control algorithm, and encouraging results have been obtained. - Author(s): S. Wu ; L. Hong ; J.R. Layne
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 429 –438
- DOI: 10.1049/ip-cta:20040694
- Type: Article
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p.
429
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(10)
Joint ground moving-target tracking identification is a crucial task in a modern combat operation. Due to the entirely different environment, ground moving-target tracking is quite different from airborne target tracking. A major difference lies in target modelling. In airborne target tracking, a target is usually treated as a point, while for ground target tracking, a target is considered a rigid body. Two approaches for 2D rigid-body target modelling are proposed. Equipped with ground moving-target indicator and high-resolution range sensors, the new approaches effectively explore the concepts of local and global motions of a rigid body. The kinematics of a global motion is described by a constant acceleration model, and a local motion is modelled by the pivoting centre and pseudocentre approaches. The proposed models are implemented by the extended Kalman filter with and without a probabilistic data association filter. The simulation results show that the proposed approaches not only correctly track a rigid-body target in a complicated scenario but also simultaneously report its structural information. - Author(s): G. Lu and D.W.C. Ho
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 439 –444
- DOI: 10.1049/ip-cta:20040490
- Type: Article
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p.
439
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(6)
The robust H∞ observer design problem is studied for a class of nonlinear discrete systems with time delay and uncertainties. The nonlinearities are assumed to satisfy global Lipschitz conditions which appear in both the dynamics and the measured output equation. The problem addressed is to design a nonlinear observer such that, for all the admissible uncertainties, the dynamics of the observer error is globally exponentially stable and has a prescribed H∞ performance. A linear matrix inequality approach is developed and a sufficient condition is obtained to design the nonlinear robust H∞ observer. Specifically, the convergent rate of the error state can be estimated by the initial condition and time delay of the system. Furthermore, robust H∞ observer designs for linear (or bilinear) discrete systems with time delay and uncertainties can be obtained directly. Finally, the effectiveness of the proposed observer design is illustrated through two numerical examples. - Author(s): Y.-C. Chang ; S.-S. Chen ; S.-F. Su ; T.-T. Lee
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 445 –452
- DOI: 10.1049/ip-cta:20040713
- Type: Article
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p.
445
–452
(8)
The simultaneous static output-feedback stabilisation problem for a collection of discrete-time interval systems with time delays both in states and in control input is considered. A sufficient condition for the existence of static output-feedback simultaneously stabilising controllers is obtained in terms of matrix spectral norms. It is shown that this problem is solvable if a corresponding matrix spectral norm assignment problem is solvable. It is also shown that the matrix spectral norm assignment problem is equivalent to a bilinear matrix inequality (BMI) problem. A sufficient condition for the BMI problem is then derived and the condition is a linear matrix inequality feasibility problem, which can be solved easily. An example is provided to demonstrate the effectiveness of the proposed methodology. - Author(s): M. Sigut ; L. Acosta ; G.N. Marichal
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 453 –459
- DOI: 10.1049/ip-cta:20040576
- Type: Article
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p.
453
–459
(7)
The study of the stability of a multifrequency system usually involves the use of nonlinear operators. It is now shown how the stability of a large-scale multifrequency system can be determined using a linear method. This is possible due to the inclusion of ‘lifting’ and ‘inverse lifting’ operators in the closed-loop system block diagram. The large-scale system under consideration is the primary mirror of the Gran Telescopio de Canarias telescope. This mirror, with a diameter of 10 m, is segmented into 36 hexagonal pieces. One strategy for the active control of the mirror consists of the simultaneous application of two control actions at different frequencies. Such a strategy is called ‘local-global’ control. Its application results in the closed-loop plant being treated as a multifrequency system. The use of the lifting operators reduces the problem to a single sampling frequency, which clearly simplifies the problem of determining the system stability. - Author(s): J. Kaloust ; C. Ham ; J. Siehling ; E. Jongekryg ; Q. Han
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 460 –464
- DOI: 10.1049/ip-cta:20040547
- Type: Article
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p.
460
–464
(5)
A nonlinear robust control design for the levitation and propulsion of a magnetic levitation (maglev) system is presented. The maglev dynamics under consideration are nonlinear and contain uncertain dynamics including negative damping due to eddy currents. The proposed recursive controller is designed using nonlinear state transformation and Lyapunov's direct method in order to guarantee global stability for the nonlinear maglev system. Simulation results are provided to show the effectiveness of the proposed control design. - Author(s): W. Xie and T. Eisaka
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 465 –472
- DOI: 10.1049/ip-cta:20040513
- Type: Article
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p.
465
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(8)
A method of designing linear-parameter varying (LPV) control systems based on the parameterisation of all quadratically stabilising controllers is presented. Conceptions of doubly coprime factorisation and Youla parameterisation of LTI systems are extended to LPV systems with respect to quadratic stability using a state-space expression. The parameterisation of closed-loop systems, which are affine with any quadratically stable Q-parameter, is then described. This description enables the application of the Q-parameter approach to a variety of LPV control-system designs. Above all, a systematic H∞ strategy is focused on and a necessary and sufficient condition and also a design scheme of Q to obtain L2-gain performance, are clarified. - Author(s): Q.-C. Zhong and C.-C. Hang
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 473 –480
- DOI: 10.1049/ip-cta:20040553
- Type: Article
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p.
473
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(8)
Using the idea of ‘shaping the control signal’, the authors generalise the time-delay-filter-based deadbeat control for processes with dead time to a two-level control so that actuator saturation is avoided. The controller mimics experienced manual operation to provide a two-level control signal. At the first stage (level), the controller outputs a value very close to the actuator saturation bound to provide the largest acceleration and then the controller outputs a smaller value to maintain the steady-state output at the same level as the set point. The system quickly settles in a finite time, which is explicitly determined by the saturation bound and is independent of the controller and (almost) of the sampling period. The disturbance response can be freely tuned according to the desired phase or gain margin. Three examples are given to show the effectiveness of the proposed controller. - Author(s): I. Kaya
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 481 –487
- DOI: 10.1049/ip-cta:20040658
- Type: Article
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p.
481
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(7)
In industrial practice, controller designs are usually performed based on an approximate model. The parameters of the physical systems can vary with operating conditions and time. Therefore it is essential to design a control system that shows a robust performance in the case of the aforementioned situations. Gain and phase margins are well-known measures for maintaining the robustness of a control system. There are many publications considering controller designs for stable processes based on gain and phase-margin specifications. However, for integrating processes, controller designs with user-specified gain and phase margins are very rare. A new two-degree-of-freedom internal model control structure is presented with simple tuning rules to design and tune PD controllers for integrating processes with a dead time to meet specified gain and phase margins. Simulation examples illustrate that the proposed design method can give better closed-loop system performance than existing design methods based on user-specified gain and phase margins. Simulation results for an assumed perturbation in the process parameters are also given to illustrate the robustness of the proposed controller structure and design method. - Author(s): G. Guo ; J.F. Qiao ; C.Z. Han
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 488 –490
- DOI: 10.1049/ip-cta:20040527
- Type: Article
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p.
488
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(3)
The controllability of both continuous and discrete periodic systems are evaluated. The controllability for continuous periodic systems is extended to unit period control, and these results are then directly extended to discrete periodic systems. An assessment is made on retaining periodic system controllability during discretisation, resulting in the conclusion that there is no loss in the controllability of linear periodic systems during discretisation when using a nonequidistant sampling pattern. - Author(s): X. Hong ; M. Brown ; S. Chen ; C.J. Harris
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 491 –498
- DOI: 10.1049/ip-cta:20040693
- Type: Article
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p.
491
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(8)
An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l1 norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram–Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach. - Author(s): P. Krishnamurthy and F. Khorrami
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 499 –510
- DOI: 10.1049/ip-cta:20040622
- Type: Article
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p.
499
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(12)
A robust adaptive nonlinear dynamic controller is designed to achieve practical stabilisation for position tracking error of a voltage-fed permanent-magnet stepper motor. The control design is an output-feedback design that utilises only rotor position measurements. Rotor velocity and stator phase currents are not available for feedback. Furthermore, the only motor parameter that is required to be known is the time constant of the electrical subsystem. Adaptations are utilised so that no other knowledge of motor parameters is required. The proposed controller is a fourth-order dynamic compensator and is robust to load torques, friction, cogging forces and other disturbances satisfying certain bounds. Practical stabilisation of the tracking error is achieved with global boundedness of all closed-loop signals. Furthermore, under the condition that the torque disturbances are locally linearly bounded by a function of rotor position, the designed controller achieves asymptotic stabilisation of the rotor position. These results can also be extended to other classes of motors. - Author(s): M.J. Grimble
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 511 –521
- DOI: 10.1049/ip-cta:20040621
- Type: Article
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p.
511
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(11)
A simple method of benchmarking filters, predictors, smoothers or condition monitoring estimators is presented, which can avoid the need for system model knowledge. A weighted least-squares estimation problem is established, where the solution is shown to involve a term that is independent of the choice of estimator and a term that can be set to zero when using the optimal estimator. The minimum estimation error cost is therefore dependent upon the independent term in the expression and these may be computed using a simple online least-squares algorithm. The level of suboptimality, reflected in the estimation error power is then readily calculable. This enables the quality of estimation to be determined for systems which may not be completely known. If an estimator is used for condition monitoring and fault detection, the benchmark enables the deterioration in the quality of estimation to be determined. It is then possible to judge when fault estimates are sufficiently reliable. Moreover, if the system is nonlinear and fault estimators are defined for different operating conditions, then the benchmark measure can be used online to determine which estimator is best and whether the estimate is optimal in a small signal change sense. - Author(s): Y.A. Zhang ; Y.A. Hu ; F.L. Lü
- Source: IEE Proceedings - Control Theory and Applications, Volume 151, Issue 4, p. 522 –524
- DOI: 10.1049/ip-cta:20040439
- Type: Article
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p.
522
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(3)
Pole-placement for SISO linear systems by state-derivative feedback
Hot strip mill multivariable mass flow control
Variable-structure control for a linear synchronous motor using a recurrent fuzzy neural network
Recurrent fuzzy neural network controller design using sliding-mode control for linear synchronous motor drive
Delay-dependent robust stability of uncertain fuzzy systems with time-varying delays
Minimising entropy and mean tracking control for affine nonlinear and non-Gaussian dynamic stochastic systems
2D rigid-body target modelling for tracking and identification with GMTI/HRR measurements
Robust H∞ observer for nonlinear discrete systems with time delay and parameter uncertainties
Simultaneous static output-feedback stabilisation for discrete-time interval systems with time delay
Determining the stability of a multifrequency large-scale system using lifting operators
Nonlinear robust control design for levitation and propulsion of a maglev system
Design of LPV control systems based on Youla parameterisation
Control of processes with dead time and input constraints using control signal shaping
Two-degree-of-freedom IMC structure and controller design for integrating processes based on gain and phase-margin specifications
Controllability of periodic systems: continuous and discrete
Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality
Voltage-fed permanent-magnet stepper motor control via position-only feedback
Data driven weighted estimation error benchmarking for estimators and condition monitoring systems
Comment: Robust adaptive sliding mode control using fuzzy modelling for a class of uncertain MIMO nonlinear systems
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